IEEE Transactions on Fuzzy Systems, Volume 22, Number 1 February 2014

1. Observer-Based Adaptive Decentralized Fuzzy Fault-Tolerant Control of Nonlinear Large-Scale Systems With Actuator Failures
Author(s): S. Tong, B. Huo, and Y. Li
Pages: 1-15

2. A New Possibilistic Programming Approach For Solving Fuzzy Multiobjective Assignment Problem
Author(s): P. Gupta and M. K. Mehlawat
Pages: 16-34

3. Consistency Measures for Hesitant Fuzzy Linguistic Preference Relations
Author(s): B. Zhu and Z. Xu
Pages: 35-45

4. Probabilistically Weighted OWA Aggregation
Author(s): R. R. Yager and N. Alajlan
Pages: 46-56

5. The Parameter Reduction of the Interval-Valued Fuzzy Soft Sets and Its Related Algorithms
Author(s): X. Ma, H. Qin, N. Sulaiman, T. Herawan, and J.H. Abawajy
Pages: 57-71

6. EFIS—Evolving Fuzzy Image Segmentation
Author(s): A. A. Othman, H. R. Tizhoosh, and F. Khalvati
Pages: 72-82

7. Some Hamacher Aggregation Operators Based on the Interval-Valued Intuitionistic Fuzzy Numbers and Their Application to Group Decision Making
Author(s): P. Liu
Pages: 83-97

8. Fuzzy Clustering With a Modified MRF Energy Function for Change Detection in Synthetic Aperture Radar Images
Author(s): M.Gong, L.Su, M.Jia, and W.Chen
Pages: 98-109

9. Linguistic Prototypes for Data From Eldercare Residents
Author(s): A. Wilbik, J. M. Keller, and J. C. Bezdek
Pages: 110-123

10. Stability and Stabilization of Discrete-Time T–S Fuzzy Systems With Stochastic Perturbation and Time-Varying Delay
Author(s): X. Yang, L. Wu, H.-K .Lam, and X. Su
Pages: 124-138

11. Fault Detection for T–S Fuzzy Systems With Unknown Membership Functions
Author(s): X.-J. Li and G.-H. Yang
Pages: 139-152

12. Sampled-Data Fuzzy Control of Chaotic Systems Based on a T–S Fuzzy Model
Author(s): Z.-G. Wu, P. Shi, H. Su, and J. Chu
Pages: 153-163

13. Adaptive Fuzzy Robust Output Feedback Control of Nonlinear Systems With Unknown Dead Zones Based on a Small-Gain Approach
Author(s): Y. Li, S. Tong, Y. Liu, and T. Li
Pages: 164-176

14. Amount of Information and Attitudinal-Based Method for Ranking Atanassov’s Intuitionistic Fuzzy Values
Author(s): K. Guo
Pages: 177-188

15. H-∞ Fuzzy Control With Randomly Occurring Infinite Distributed Delays and Channel Fadings
Author(s): S. Zhang, Z. Wang, D. Ding, and H. Shu
Pages: 189-200

16. An Agent-Based Fuzzy Collaborative Intelligence Approach for Precise and Accurate Semiconductor Yield Forecasting
Author(s): T. Chen and Y.-C. Wang
Pages: 201-211

17. On Energy-to-Peak Filtering for Nonuniformly Sampled Nonlinear Systems: A Markovian Jump System Approach
Author(s): H. Zhang, Y. Shi, and J. Wang
Pages: 212-222

18. Stability Analysis of Polynomial-Fuzzy-Model-Based Control Systems With Mismatched Premise Membership Functions
Author(s): H.K. Lam and S.-H. Tsai
Pages: 223-229

19. Comments on “Finite-Time H-∞ Fuzzy Control of Nonlinear Jump Systems With Time Delays Via Dynamic Observer-Based State Feedback”
Author(s): Y. Zhang, C. Liu, and H. R. Karimi
Pages: 230

Neural Networks new articles 20 January - 26 January, 2014

1. Policy oscillation is overshooting
Paul Wagner
   
2. NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
Nikola K. Kasabov

Neural Networks, Volume 51, March 2014

1. Editorial Board  
Pages IFC

Neuroscience

2. Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks  
Pages: 1-8
Author(s): Jiejie Chen, Zhigang Zeng, Ping Jiang
   

Learning Systems

3. Feature selection and multi-kernel learning for sparse representation on a manifold  
Pages: 9-16
Author(s):Jim Jing-Yan Wang, Halima Bensmail, Xin Gao
   
4. Long-term time series prediction using OP-ELM
Pages: 50-56
Author(s):Alexander Grigorievskiy, Yoan Miche, Anne-Mari Ventelä, Eric Séverin, Amaury Lendasse
   
5. Least Square Fast Learning Network for modeling the combustion efficiency of a 300WM coal-fired boiler
Pages: 57-66
Author(s):Guoqiang Li, Peifeng Niu, Huaibao Wang, Yongchao Liu
   

Mathematical and Computational Analysis

6. Neural network for solving convex quadratic bilevel programming problems 
Pages: 17-25
Author(s):Xing He, Chuandong Li, Tingwen Huang, Chaojie Li
   
7. Stability analysis of switched stochastic neural networks with time-varying delays  
Pages: 39-49
Author(s):Xiaotai Wu, Yang Tang, Wenbing Zhang
   
8. Lagrangian support vector regression via unconstrained convex minimization  
Pages: 67-79
Author(s):S. Balasundaram, Deepak Gupta, Kapil
   
9. Periodicity and global exponential stability of generalized Cohen–Grossberg neural networks with discontinuous activations and mixed delays
Pages: 80-95
Author(s):Dongshu Wang, Lihong Huang
   

Engineering and Applications

10. A generalized analog implementation of piecewise linear neuron models using CCII building blocks  
Pages: 26-38
Author(s):Hamid Soleimani, Arash Ahmadi, Mohammad Bavandpour, Ozra Sharifipoor
   
11. Current Events  
Pages I-II

Reminder: paper submission deadline for KES 2014

A reminder that the deadline for submitting papers to the 18th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES) 2014 is 15 March, 2014. This conference will be held in Gdynia, Poland, 15-17 September, 2014.

IEEE Transactions on Neural Networks and Learning Systems, Volume 25, Issue 2, February 2014

1. What Are the Differences Between Bayesian Classifiers and Mutual-Information Classifiers?
Author(s): Bao-Gang Hu
Pages: 249 - 264

2. Multikernel Least Mean Square Algorithm
Author(s): Felipe A. Tobar; Sun-Yuan Kung; Danilo P. Mandic
Pages: 265 - 277

3. Quantum Neural Network-Based EEG Filtering for a Brain-Computer Interface
Author(s): Vaibhav Gandhi; Girijesh Prasad; Damien Coyle; Laxmidhar Behera; Thomas Martin McGinnity
Pages: 278 - 288

4. Multiclass From Binary: Expanding One-Versus-All, One-Versus-One and ECOC-Based Approaches
Author(s): Anderson Rocha; Siome Klein Goldenstein
Pages: 289 - 302

5. Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals
Author(s): Hao Quan; Dipti Srinivasan; Abbas Khosravi
Pages: 303 - 315

6. HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters
Author(s): Kirill Minkovich; Corey M. Thibeault; Michael John O’Brien; Aleksey Nogin; Youngkwan Cho; Narayan Srinivasa
Pages: 316 - 331

7. Sliding-Mode Control Design for Nonlinear Systems Using Probability Density Function Shaping
Author(s): Yu Liu; Hong Wang; Chaohuan Hou
Pages: 332 - 343

8. Nanophotonic Reservoir Computing With Photonic Crystal Cavities to Generate Periodic Patterns
Author(s): Martin Andre Agnes Fiers; Thomas Van Vaerenbergh; Francis Wyffels; David Verstraeten; Benjamin Schrauwen; Joni Dambre; Peter Bienstman
Pages: 344 - 355

9. Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection
Author(s): Huanhuan Chen; Peter Tino; Xin Yao
Pages: 356 - 369

10. Zhang Neural Network for Online Solution of Time-Varying Linear Matrix Inequality Aided With an Equality Conversion
Author(s): Dongsheng Guo; Yunong Zhang
Pages: 370 - 382

11. Robust Pole Assignment for Synthesizing Feedback Control Systems Using Recurrent Neural Networks
Author(s): Xinyi Le; Jun Wang
Pages: 383 - 393

12. Efficient Dual Approach to Distance Metric Learning
Author(s): Chunhua Shen; Junae Kim; Fayao Liu; Lei Wang; Anton van den Hengel
Pages: 394 - 406

13. Event-Based Visual Flow
Author(s): Ryad Benosman; Charles Clercq; Xavier Lagorce; Sio-Hoi Ieng; Chiara Bartolozzi
Pages: 407 - 417

14. Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach
Author(s): Derong Liu; Ding Wang; Hongliang Li
Pages: 418 - 428

15. Novel Adaptive Strategies for Synchronization of Linearly Coupled Neural Networks With Reaction-Diffusion Terms
Author(s): Jin-Liang Wang; Huai-Ning Wu; Lei Guo
Pages: 429 - 440

IEEE Transactions on Computational Intelligence and AI in Games, Volume 5, Number 4, December 2013

1. A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft
Author(s): Ontanon, S. ; Synnaeve, G. ; Uriarte, A. ; Richoux, F. ; Churchill, D. ; Preuss, M.
Pages: 293-311

2. Repeated Goofspiel: A Game of Pure Strategy
Author(s):Dror, M. ; Kendall, G.
Pages: 312-324

3. A Heuristic-Based Planner and Improved Controller for a Two-Layered Approach for the Game of Billiards
Author(s):Landry, J.-F. ; Dussault, J.-P. ; Mahey, P.
Pages: 325-336

4. Automated 3-D Animation From Snooker Videos With Information-Theoretical Optimization
Author(s):Jiang, R. ; Parry, M.L. ; Legg, P.A. ; Chung, D.H.S. ; Griffiths, I.W.
Pages: 337-345

5. Incentive Learning in Monte Carlo Tree Search
Author(s):Kao, K.-Y. ; Wu, I-C. ; Yen, S.-J. ; Shan, Y.-C.
Pages: 346-352

IEEE Transactions on Autonomous Mental Development, Volume 5, Number 4, December 2013

1. Computational Audiovisual Scene Analysis in Online Adaptation of Audio-Motor Maps
Author(s): Yan, R. ; Rodemann, T. ; Wrede, B.
Pages: 273-287

2. Modeling Cross-Modal Interactions in Early Word Learning
Author(s): Althaus, N. ; Mareschal, D.
Pages: 288-297

3. Learning to Reproduce Fluctuating Time Series by Inferring Their Time-Dependent Stochastic Properties: Application in Robot Learning Via Tutoring
Author(s): Murata, S. ; Namikawa, J. ; Arie, H. ; Sugano, S. ; Tani, J.
Pages: 298-310

4. Conceptual Imitation Learning Based on Perceptual and Functional Characteristics of Action
Author(s): Hajimirsadeghi, H. ; Ahmadabadi, M.N. ; Araabi, B.N.
Pages: 311-325

5. A Robotic Model of Reaching and Grasping Development
Author(s): Savastano, P. ; Nolfi, S.
Pages: 326-337

Neural Networks new articles 6 January -12 January, 2014

1. Nonsmooth finite-time stabilization of neural networks with discontinuous activations  
Xiaoyang Liu, Ju.H. Park, Nan Jiang, Jinde Cao

Neural Networks new articles 23 December - 29 December, 2013

1. Construction of a Boolean model of gene and protein regulatory network with memory
Meng Yang, Rui Li, Tianguang Chu
   
2. Pairwise constrained concept factorization for data representation
Yangcheng He, Hongtao Lu, Lei Huang, Saining Xie
   
3. Periodicity and global exponential stability of a generalized Cohen–Grossberg neural networks with discontinuous activations and mixed delays
Dongshu Wang, Lihong Huang

IEEE Transactions on Neural Networks and Learning Systems: Volume 25, Issue 1, January 2014

1. Guest Editorial: Learning in Nonstationary and Evolving Environments
Author(s): Robi Polikar; Cesare Alippi
Pages: 9 - 11

2. COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data
Author(s): Karl B. Dyer; Robert Capo; Robi Polikar
Pages: 12 - 26

3. Active Learning With Drifting Streaming Data
Author(s): Indre Zliobaite; Albert Bifet; Bernhard Pfahringer; Geoffrey Holmes
Pages: 27 - 39

4. Online Bayesian Learning With Natural Sequential Prior Distribution
Author(s): Yohei Nakada; Makio Wakahara; Takashi Matsumoto
Pages: 40 - 54

5. PANFIS: A Novel Incremental Learning Machine
Author(s): Mahardhika Pratama; Sreenatha. G. Anavatti; Plamen. P. Angelov; Edwin Lughofer
Pages: 55 - 68

6. PCA Feature Extraction for Change Detection in Multidimensional Unlabeled Data
Author(s): Ludmila I. Kuncheva; William J. Faithfull
Pages: 69 - 80

7. Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm
Author(s): Dariusz Brzezinski; Jerzy Stefanowski
Pages: 81 - 94

8. Mining Recurring Concepts in a Dynamic Feature Space
Author(s): Joao Bartolo Gomes; Mohamed Medhat Gaber; Pedro A. C. Sousa; Ernestina Menasalvas
Pages: 95 - 110

9. Dynamic Learning From Adaptive Neural Network Control of a Class of Nonaffine Nonlinear Systems
Author(s): Shi-Lu Dai; Cong Wang; Min Wang
Pages: 111 - 123

10. Learning in the Model Space for Cognitive Fault Diagnosis
Author(s): Huanhuan Chen; Peter Tino; Ali Rodan; Xin Yao
Pages: 124 - 136

11. Adaptive Approximation for Multiple Sensor Fault Detection and Isolation of Nonlinear Uncertain Systems
Author(s): Vasso Reppa; Marios M. Polycarpou; Christos G. Panayiotou
Pages: 137 - 153

12. Dealing With Concept Drifts in Process Mining
Author(s): R. P. Jagadeesh Chandra Bose; Wil M. P. van der Aalst; Indre Zliobaite; Mykola Pechenizkiy
Pages: 154 - 171

13. Adaptive Convex Combination Approach for the Identification of Improper Quaternion Processes
Author(s): Bukhari Che Ujang; Cyrus Jahanchahi; Clive Cheong Took; Danilo P. Mandic
Pages: 172 - 182

14. Developmental Perception of the Self and Action
Author(s): Ryo Saegusa; Giorgio Metta; Giulio Sandini; Lorenzo Natale
Pages: 183 - 202

15. Linguistic Decision Making for Robot Route Learning
Author(s): Hongmei He; Thomas Martin McGinnity; Sonya Coleman; Bryan Gardiner
Pages: 203 - 215

16. An Interval Type-2 Neural Fuzzy Chip With On-Chip Incremental Learning Ability for Time-Varying Data Sequence Prediction and System Control
Author(s): Chia-Feng Juang; Chi-You Chen
Pages: 216 - 228

17. Learning Geotemporal Nonstationary Failure and Recovery of Power Distribution
Author(s): Yun Wei; Chuanyi Ji; Floyd Galvan; Stephen Couvillon; George Orellana; James Momoh
Pages: 229 - 240

18. Continuous Dynamical Combination of Short and Long-Term Forecasts for Nonstationary Time Series
Author(s): Domingos Savio Pereira Salazar; Paulo Jorge Leitao Adeodato; Adrian Lucena Arnaud
Pages: 241 - 246

Neural Networks Volume 50 Pages 1-182 February 2014

Neural Networks Letters

1. Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks 
Pages: 98-109
Author(s): Ancai Zhang, Jianlong Qiu, Jinhua She

2. Cellular computational networks—A scalable architecture for learning the dynamics of large networked systems 
Pages: 120-123
Author(s): Bipul Luitel, Ganesh Kumar Venayagamoorthy

Cognitive Science

3. Supervised orthogonal discriminant subspace projects learning for face recognition  
Pages: 33-46
Author(s): Yu Chen, Xiao-Hong Xu

Learning Systems

4. Direct Kernel Perceptron (DKP): Ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation 
Pages: 60-71
Author(s): Manuel Fernández-Delgado, Eva Cernadas, Senén Barro, Jorge Ribeiro, José Neves

5. Batch gradient method with smoothing image regularization for training of feedforward neural networks  
Pages: 72-78
Author(s): Wei Wu, Qinwei Fan, Jacek M. Zurada, Jian Wang, Dakun Yang, Yan Liu

6. Compressed classification learning with Markov chain samples 
Pages: 90-97
Author(s): Feilong Cao, Tenghui Dai, Yongquan Zhang, Yuanpeng Tan

7. Semi-supervised learning of class balance under class-prior change by distribution matching  
Pages: 110-119
Author(s): Marthinus Christoffel du Plessis, Masashi Sugiyama

8. Robust support vector machine-trained fuzzy system  
Pages: 154-165
Author(s): Yahya Forghani, Hadi Sadoghi Yazdi

9. Large-scale linear nonparallel support vector machine solver  
Pages: 166-174
Author(s): Yingjie Tian, Yuan Ping

10. Finite time convergent learning law for continuous neural networks  
Pages: 175-182
Author(s): Isaac Chairez
   

Mathematical and Computational Analysis

11. A Bayesian inverse solution using independent component analysis  
Pages: 47-59
Author(s): Jouni Puuronen, Aapo Hyvärinen
   
12. A one-layer recurrent neural network for constrained nonsmooth invex optimization  
Pages: 79-89
Author(s): Guocheng Li, Zheng Yan, Jun Wang
   
13. Pointwise probability reinforcements for robust statistical inference  
Pages: 124-141
Author(s): Benoît Frénay, Michel Verleysen
   
14. A linear recurrent kernel online learning algorithm with sparse updates  
Pages: 142-153
Author(s): Haijin Fan, Qing Song

Engineering and Applications

15. Correcting and combining time series forecasters  
Pages: 1-11
Author(s): Paulo Renato A. Firmino, Paulo S.G. de Mattos Neto, Tiago A.E. Ferreira

16. Hybrid fault diagnosis of nonlinear systems using neural parameter estimators 
Pages: 12-32
Author(s): E. Sobhani-Tehrani, H.A. Talebi, K. Khorasani

Work-Life Balance

A video of a panel session of two young(ish) professors, talking about work-life balance. I used to work in the same lab as Corey Bradshaw, and have even published with him. He is a straight-speaking person who says what he thinks, so you can be sure that what he says in this session is his honest opinion. That being said, I do have some conflicted feelings about this discussion.



On the one hand, I respect and envy their academic achievements. On the other hand, the sacrifices they have made to get where they are are just terrifying, and strike me as selfish. When Tanya Munro talks about dragging her two tiny babies to a conference, or skipping their end-of-year performance, or both of them talking about leaving their kids at home for the evening again, I can't help but think that that is just so much macho bullsh*t. For me, family comes first, there is no choice. My daughter is smart without being conceited, brave without being reckless, strong without being over-bearing, loving, caring and empathetic, without being clingy. She wouldn't be those things if she didn't have an extended family around her who were fully engaged in her upbringing. I'd rather be a "less-successful" academic, than risk losing what I have with her. She'll grow up soon enough, I can put more energy into my career then. Certainly I could achieve more if I sacrificed more, or if I slept a lot less, but if I worked an 80-hour week, I would die. It's as simple as that. One of the last things my father said to me, just a few days before he died, was "you're not a machine". I refuse to risk depriving my wife of her husband and my daughter of her father.

Another point at which I disagree with Corey is when he mentions telling his post-docs "Start publishing papers or I'm going to have to sack you". I think this is a poor management technique: if someone isn't performing, you as a manager must coach them to lift their game. Management by fear is a poor technique and just breeds resentment. Life may be too short to work with a*holes, but it's also too short to accumulate enemies.

The idea that everything you do should lead to an obvious paper is fine for someone who in only doing research, but personally I couldn't live without undergraduate teaching. I need the surge of energy I get from standing in front of a class and explaining complex concepts. I really love it when someone "gets it", when their face lights up with understanding. Even though I spend most of my time now in management, I'd never take another position where I wasn't teaching.

Finally, everyone's circumstances are different, so you shouldn't compare yourself to others. Tanya Munro may have met her husband during her first year of university, but I met my wife at 28, married her just before turning 30, and had my daughter, finished my PhD, and started my first post-doc at 31. I had problems with my PhD topic, I had health problems, and I had to work to support myself. Now I'm 40 and my career path is finally starting to settle down. I may have achieved less academically than them, but so have most people. What, really, does comparing myself to them achieve? Nothing, except perhaps to make me feel badly about myself.

One thing I do agree with is that you have to find your own balance, your own way. I think I've found mine, and I'm happier for it. The video is well worth the time to view it, if only to gain some perspectives from successful academics.

WCCI 2014 Deadline Extension

The deadline for submitting papers to the World Congress on Computational Intelligence (WCCI) 2014 has been extended to the 20th of January, 2014. There will be no further extensions. This conference combines the three major conferences of the IEEE Computational Intelligence Society: The International Joint Conference on Neural Networks (IJCNN); the Congress on Evolutionary Computation (CEC) and the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). This conference will be held in Beijing, China, July 6-11, 2014.

Reminder: paper submission deadline for EAIS 2014

A reminder that the deadline for submitting papers to the IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) 2014 is January 15, 2014. This conference will be held in Linz, Austria, June 2-4, 2014.

Reminder: paper submission deadline for IEEE SSCI 2014

A reminder that the deadline for submitting papers to the IEEE Symposium Series on Computational Intelligence (SSCI) 2014 is 15 June 2014. This group of symposia will be held in Orlando, Florida, 9-12 December, 2014.

Call for papers: Special Session for WCCI 2014 "Applications of Computational lntelligence in Ecological Informatics and Environmental Modelling"

Aim

The aim of this special session is to provide a forum for recent research in the application of computational intelligence in the areas of ecological informatics, ecological modelling and environmental modelling.

Ecological informatics and the related field of ecological modelling involve constructing computational models of ecological systems. These models include such things as the distribution or abundance of particular species, models of the interaction between multiple species, and models of the future development of populations. Environmental modelling is closely related and involves constructing models of the physical environment that biological eco-systems inhabit. These models cover such topics as the climate and climate change and the detection of landscape features from geographical data. Models have also been constructed of such environmental topics as waste management systems, water quality and drainage systems and air pollution. As these are highly-complex systems, algorithms from the field of computational intelligence have already been widely applied to modelling this data. Previous work has successfully applied artificial neural networks, fuzzy systems, evolutionary algorithms, support vector machines and combinations of these including neuro-fuzzy and neuro-evolutionary approaches. In each case, computational intelligence methods were shown to be more effective at solving the problem than the alternative methods.

Scope

Topics relevant to this special session include, but are not limited to, the following applications of computational intelligence, including Artificial Neural Networks, Fuzzy Systems, and Evolutionary Algorithms:

•    Species distribution and ecological niche modelling
•    Predicting species abundance
•    Remote sensing image analysis and content-based image retrieval for Ecological Informatics and Environmental Modelling
•    Analysis of species assemblages
•    Issues in the preparation of ecological data for modelling
•    Modelling of pollutants in air, land or water
•    Modelling water quality
•    Predicting the effects of climate change
•    Predicting crop hazards, pests or diseases
•    Identifying landscape features
•    Modelling ecosystem biomass

Deadline

The deadline for submissions to this special session is 20 January 2014.

Information for Authors

1)    Information on the format and templates for papers can be found here:
       http://www.ieee-wcci2014.org/Paper%20Submission.htm
2)    Papers should be submitted via the IJCNN 2014 paper submission site:
       http://ieee-cis.org/conferences/ijcnn2014/upload.php3)
       Select the Special Session name in the Main Research topic dropdown list
4)    Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of December 20, 2013

Organisers

•    Dr Michael J Watts, AIS St Helens, Auckland, New Zealand. mjwatts@ieee.org
•    Associate Professor Russel Pears, Auckland University of Technology, Auckland, New Zealand, russel.pears@aut.ac.nz
•    Professor Jie Yang, Shanghai Jiao Tong University, Shanghai, China, jieyang@sjtu.edu.cn

IEEE Transactions on Fuzzy Systems, Volume 21, Number 6, December 2013

1. An Improved Estimation Method for Unmodeled Dynamics Based on ANFIS and Its Application to Controller Design
Author(s): Zhang, Y. ; Chai, T. ; Wang, H. ; Chen, X. ; Su, C.-Y.
Pages: 989-1005

2. Linguistic Computational Model Based on 2-Tuples and Intervals
Author(s): Dong, Y. ; Zhang, G. ; Hong, W.-C. ; Yu, S.
Pages: 1006-1018

3. Dynamic Fuzzy Clustering and Its Application in Motion Segmentation
Author(s): Nguyen, T.M. ; Wu, Q.M.J.
Pages: 1019-1031

4. Hierarchical Structured Sparse Representation for T–S Fuzzy Systems Identification
Author(s): Luo, M. ; Sun, F. ; Liu, H.
Pages: 1032-1043

5. Intelligent Hybrid Control System Design for Antilock Braking Systems Using Self-Organizing Function-Link Fuzzy Cerebellar Model Articulation Controller
Author(s): Lin, C.-M. ; Li, H.-Y.
Pages: 1044-1055

6. Simplified Interval Type-2 Fuzzy Logic Systems
Author(s): Mendel, J.M. ; Liu, X.
Pages: 1056-1069

7. Statistical Inference of Rough Set Dependence and Importance Analysis
Author(s): Hu, D. ; Yu, X.
Pages: 1070-1079

8. A Metacognitive Neuro-Fuzzy Inference System (McFIS) for Sequential Classification Problems
Author(s): Subramanian, K. ; Suresh, S. ; Sundararajan, N.
Pages: 1080-1095

9. Strongest Strong Cycles and $theta$-Fuzzy Graphs
Author(s): Mathew, S. ; Sunitha, M.S.
Pages: 1096-1104

10. Functional Machine With Takagi–Sugeno Inference to Coordinated Movement in Underwater Vehicle-Manipulator Systems
Author(s): dos Santos, C.H.F. ; De Pieri, E.R.
Pages: 1105-1114

11. Human Reliability Evaluation for Offshore Platform Musters Using Intuitionistic Fuzzy Sets
Author(s): Tyagi, S.K. ; Akram, M.
Pages: 1115-1122

12. Enhanced Adaptive Fuzzy Control With Optimal Approximation Error Convergence
Author(s): Pan, Y. ; Er, M.J.
Pages: 1123-1132

13. FINGRAMS: Visual Representations of Fuzzy Rule-Based Inference for Expert Analysis of Comprehensibility
Author(s): Pancho, D.P. ; Alonso, J.M. ; Cordon, O. ; Quirin, A. ; Magdalena, L.
Pages: 1133-1149

14. A New Approach to Interval-Valued Choquet Integrals and the Problem of Ordering in Interval-Valued Fuzzy Set Applications
Author(s): Bustince, H. ; Galar, M. ; Bedregal, B. ; Kolesarova, A. ; Mesiar, R.
Pages: 1150-1162

15. Defuzzification Functionals of Ordered Fuzzy Numbers
Author(s): Kosinski, W. ; Prokopowicz, P. ; Rosa, A.
Pages: 1163-1169

16. A Soft Modularity Function For Detecting Fuzzy Communities in Social Networks
Author(s): Havens, T.C. ; Bezdek, J.C. ; Leckie, C. ; Ramamohanarao, K. ; Palaniswami, M.
Pages: 1170-1175

IEEE Transactions on Evolutionary Computation, Volume 17, Number 6, December 2013

1. Striking a Mean- and Parent-Centric Balance in Real-Valued Crossover Operators
Author(s): Someya, H.
Pages: 737-754

2. Multiobjective Particle Swarm Optimization With Preference-Based Sort and Its Application to Path Following Footstep Optimization for Humanoid Robots
Author(s): Lee, K.-B. ; Kim, J.-H.
Pages: 755-766

3. An Energy-Based Sampling Technique for Multi-Objective Restricted Boltzmann Machine
Author(s): Shim, V.A. ; Tan, K.C. ; Cheong, C.Y.
Pages: 767-785

4. An Efficient Evolutionary Algorithm for Chance-Constrained Bi-Objective Stochastic Optimization
Author(s): Liu, B. ; Zhang, Q. ; Fernandez, F.V. ; Gielen, G.G.E.
Pages: 786-796

5. Scaling Up Estimation of Distribution Algorithms for Continuous Optimization
Author(s): Dong, W. ; Chen, T. ; Tino, P. ; Yao, X.
Pages: 797-822

6. Optimal Cycle Program of Traffic Lights With Particle Swarm Optimization
Author(s): Garcia-Nieto, J. ; Olivera, A.C. ; Alba, E.
Pages: 823-839

7. Grammatical Evolution Hyper-Heuristic for Combinatorial Optimization Problems
Author(s): Sabar, N.R. ; Ayob, M. ; Kendall, G. ; Qu, R.
Pages: 840-861

8. Fitness Modeling With Markov Networks
Author(s): Brownlee, A.E.I. ; McCall, J.A.W. ; Zhang, Q.
Pages: 862-879

Neural Networks Volume 48 Pages 1-208

Neural Networks Letters

1. Is mutual information adequate for feature selection in regression?  
Pages: 1-7
Author(s): Benoît Frénay, Gauthier Doquire, Michel Verleysen
   
2. Neural architecture design based on extreme learning machine  
Pages: 19-24
Author(s): Andrés Bueno-Crespo, Pedro J. García-Laencina, José-Luis Sancho-Gómez
   
3. Comments on the “No-Prop” algorithm  
Pages: 59-60
Author(s): Meng-Hiot Lim

4. Exponential stabilization of delayed recurrent neural networks: A state estimation based approach  
Pages: 153-157
Author(s): He Huang, Tingwen Huang, Xiaoping Chen, Chunjiang Qian

Neuroscience

5. A model of task-specific focal dystonia  
Pages: 25-31
Author(s): Eckart Altenmüller, Dieter Müller

6. Global exponential synchronization of memristor-based recurrent neural networks with time-varying delays  
Pages: 195-203
Author(s): Shiping Wen, Gang Bao, Zhigang Zeng, Yiran Chen, Tingwen Huang
   

Learning Systems

7. An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion 
Pages: 8-18
Author(s): Yuanyuan Liu, L.C. Jiao, Fanhua Shang, Fei Yin, F. Liu

8. Analysis of programming properties and the row–column generation method for 1-norm support vector machines 
Pages: 32-43
Author(s): Li Zhang, WeiDa Zhou

9. Fully corrective boosting with arbitrary loss and regularization  
Pages: 44-58
Author(s): Chunhua Shen, Hanxi Li, Anton van den Hengel
   
10. Fixed-final-time optimal control of nonlinear systems with terminal constraints  
Pages: 61-71
Author(s): Ali Heydari, S.N. Balakrishnan
   
11. Solving graph data issues using a layered architecture approach with applications to web spam detection
Pages: 78-90
Author(s): Franco Scarselli, Ah Chung Tsoi, Markus Hagenbuchner, Lucia Di Noi
   
12. Fuzzy rough sets, and a granular neural network for unsupervised feature selection 
Pages: 91-108
Author(s): Avatharam Ganivada, Shubhra Sankar Ray, Sankar K. Pal
   
13. Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule  
Pages: 109-124
Author(s): Michael Beyeler, Nikil D. Dutt, Jeffrey L. Krichmar
   
14. 1-norm support vector novelty detection and its sparseness  
Pages: 125-132
Author(s): Li Zhang, WeiDa Zhou
   
15. On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning  
Pages: 173-179
Author(s): Dansong Cheng, Minh Nhut Nguyen, Junbin Gao, Daming Shi
   

Mathematical and Computational Analysis

16. Multivariate neural network operators with sigmoidal activation functions 
Pages: 72-77
Author(s): Danilo Costarelli, Renato Spigler
   
17. Self-Organizing Hidden Markov Model Map (SOHMMM) 
Pages: 133-147
Author(s): Christos Ferles, Andreas Stafylopatis
   
18. The breaking of a delayed ring neural network contributes to stability: The rule and exceptions 
Pages: 148-152
Author(s): T.N. Khokhlova, M.M. Kipnis
   
19. Global exponential dissipativity and stabilization of memristor-based recurrent neural networks with time-varying delays  
Pages: 158-172
Author(s): Zhenyuan Guo, Jun Wang, Zheng Yan
   
20. Dynamical behaviors for discontinuous and delayed neural networks in the framework of Filippov differential inclusions  
Pages: 180-194
Author(s): Lihong Huang, Zuowei Cai, Lingling Zhang, Lian Duan
   

Letter to the Editor

21. Reply to the Comments on the “No-Prop” algorithm  
Pages: 204
Author(s): Bernard Widrow
   
22. A comment on “ image -stability and image -synchronization for fractional-order neural networks”  
Pages: 207-208
Author(s): Li Kexue, Peng Jigen, Gao Jinghuai
   

Erratum

23. Erratum to “Comments on the ‘No-Prop’ algorithm” [Neural Netw. 48 (2013) 59–60]  
Pages: 205
Author(s): Meng-Hiot Lim
   

Corrigendum

24. Corrigendum to “Noise enhanced clustering and competitive learning algorithms” [Neural Netw. 37 (2013) 132–140]  
Pages: 206
Author(s): Osonde Osoba, Bart Kosko

Neural Networks new articles 25 November - 1 December, 2013

1. Feature selection and multi-kernel learning for sparse representation on a manifold
Jim Jing-Yan Wang, Halima Bensmail, Xin Gao

2. Large-scale linear Nonparallel Support Vector Machine solver
Yingjie Tian, Yuan Ping

3. Neural network for solving convex quadratic bilevel programming problems
Xing He, Chuandong Li, Tingwen Huang, Chaojie Li

Neural Networks new articles 19-25 November, 2013

1. Compressed classification learning with Markov chain samples 
Feilong Cao, Tenghui Dai, Yongquan Zhang, Yuanpeng Tan
   
2. Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks  
Ancai Zhang, Jianlong Qiu, Jinhua She

3. Pointwise probability reinforcements for robust statistical inference 
Benoît Frénay, Michel Verleysen

4. Robust support vector machine-trained fuzzy system
Yahya Forghani, Hadi Sadoghi Yazdi

5. A linear recurrent kernel online learning algorithm with sparse updates 
Haijin Fan, Qing Song
   
6. A one-layer recurrent neural network for constrained nonsmooth invex optimization 
Guocheng Li, Zheng Yan, Jun Wang

7. Semi-supervised learning of class balance under class-prior change by distribution matching
Marthinus Christoffel du Plessis, Masashi Sugiyama
   
8. Batch gradient method with smoothing image regularization for training of feedforward neural networks
Wei Wu, Qinwei Fan, Jacek M. Zurada, Jian Wang, Dakun Yang, Yan Liu

Call for papers: Special Session for WCCI 2014 "Applications of Computational lntelligence in Ecological Informatics and Environmental Modelling"

Aim

The aim of this special session is to provide a forum for recent research in the application of computational intelligence in the areas of ecological informatics, ecological modelling and environmental modelling.

Ecological informatics and the related field of ecological modelling involve constructing computational models of ecological systems. These models include such things as the distribution or abundance of particular species, models of the interaction between multiple species, and models of the future development of populations. Environmental modelling is closely related and involves constructing models of the physical environment that biological eco-systems inhabit. These models cover such topics as the climate and climate change and the detection of landscape features from geographical data. Models have also been constructed of such environmental topics as waste management systems, water quality and drainage systems and air pollution. As these are highly-complex systems, algorithms from the field of computational intelligence have already been widely applied to modelling this data. Previous work has successfully applied artificial neural networks, fuzzy systems, evolutionary algorithms, support vector machines and combinations of these including neuro-fuzzy and neuro-evolutionary approaches. In each case, computational intelligence methods were shown to be more effective at solving the problem than the alternative methods.

Scope

Topics relevant to this special session include, but are not limited to, the following applications of computational intelligence, including Artificial Neural Networks, Fuzzy Systems, and Evolutionary Algorithms:

•    Species distribution and ecological niche modelling
•    Predicting species abundance
•    Remote sensing image analysis and content-based image retrieval for Ecological Informatics and Environmental Modelling
•    Analysis of species assemblages
•    Issues in the preparation of ecological data for modelling
•    Modelling of pollutants in air, land or water
•    Modelling water quality
•    Predicting the effects of climate change
•    Predicting crop hazards, pests or diseases
•    Identifying landscape features
•    Modelling ecosystem biomass

Deadline

The deadline for submissions to this special session is 20 December 2013.

Information for Authors

1)    Information on the format and templates for papers can be found here:
       http://www.ieee-wcci2014.org/Paper%20Submission.htm
2)    Papers should be submitted via the IJCNN 2014 paper submission site:
       http://ieee-cis.org/conferences/ijcnn2014/upload.php3)
       Select the Special Session name in the Main Research topic dropdown list
4)    Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of December 20, 2013

Organisers

•    Dr Michael J Watts, AIS St Helens, Auckland, New Zealand. mjwatts@ieee.org
•    Associate Professor Russel Pears, Auckland University of Technology, Auckland, New Zealand, russel.pears@aut.ac.nz
•    Professor Jie Yang, Shanghai Jiao Tong University, Shanghai, China, jieyang@sjtu.edu.cn

IEEE Transactions on Neural Networks and Learning Systems: Volume 24, Issue 12, December 2013

1. Canonical Correlation Analysis on Data With Censoring and Error Information
Author(s): Sun, J. ; Keates, S.
Pages: 1909-1919

2. Highly Accurate Moving Object Detection in Variable Bit Rate Video-Based Traffic Monitoring Systems
Author(s): Huang, S.-C. ; Chen, B.-H.
Pages: 1920-1931

3. Recurrent Neural Collective Classification
Author(s): Monner, D.D. ; Reggia, J.A.
Pages: 1932-1943

4. Online Selective Kernel-Based Temporal Difference Learning
Author(s): Chen, X. ; Gao, Y. ; Wang, R.
Pages: 1944-1956

5. Stability and Synchronization of Discrete-Time Neural Networks With Switching Parameters and Time-Varying Delays
Author(s): Wu, L. ; Feng, Z. ; Lam, J.
Pages: 1957-1972

6. Artificial Endocrine Controller for Power Management in Robotic Systems
Author(s): Sauze, C. ; Neal, M.
Pages: 1973-1985

7. Operator Control of Interneural Computing Machines
Author(s): Shih, M.-H. ; Tsai, F.-S.
Pages: 1986-1998

8. Multiple Graph Label Propagation by Sparse Integration
Author(s): Karasuyama, M. ; Mamitsuka, H.
Pages: 1999-2012

9. Universal Blind Image Quality Assessment Metrics Via Natural Scene Statistics and Multiple Kernel Learning
Author(s): Gao, X. ; Gao, F. ; Tao, D. ; Li, X.
Pages: 2013-2026

10. H_{\infty } State Estimation for Complex Networks With Uncertain Inner Coupling and Incomplete Measurements
Author(s): Shen, B. ; Wang, Z. ; Ding, D. ; Shu, H.
Pages: 2027-2037

11. Goal Representation Heuristic Dynamic Programming on Maze Navigation
Author(s): Ni, Z. ; He, H. ; Wen, J. ; Xu, X.
Pages: 2038-2050

12. Accelerated Canonical Polyadic Decomposition Using Mode Reduction
Author(s): Zhou, G. ; Cichocki, A. ; Xie, S.
Pages: 2051-2062

13. Hardware Friendly Probabilistic Spiking Neural Network With Long-Term and Short-Term Plasticity
Author(s): Hsieh, H.-Y. ; Tang, K.-T.
Pages: 2063-2074

14. Neural Network Architecture for Cognitive Navigation in Dynamic Environments
Author(s): Villacorta-Atienza, J.A. ; Makarov, V.A.
Pages: 2075-2087

15. An Equivalence Between Adaptive Dynamic Programming With a Critic and Backpropagation Through Time
Author(s): Fairbank, M. ; Alonso, E. ; Prokhorov, D.
Pages: 2088-2100

16. Semisupervised Multitask Learning With Gaussian Processes
Author(s): Skolidis, G. ; Sanguinetti, G.
Pages: 2101-2112

17. Nonlinear Projection Trick in Kernel Methods: An Alternative to the Kernel Trick
Author(s): Kwak, N.
Pages: 2113-2119

Evolving Systems Vol 4, Issue 4, November 2013

1. Editorial: Adaptive connectionist systems for engineering applications
Author(s): Chrisina Jayne
Abstract    Full text HTML    Full text PDF

2. Neurocomputing techniques to dynamically forecast spatiotemporal air pollution data
Author(s): Antonios Papaleonidas & Lazaros Iliadis
Abstract    Full text HTML    Full text PDF

3. Information dynamics based self-adaptive reservoir for delay temporal memory tasks
Author(s): Sakyasingha Dasgupta , Florentin Wörgötter & Poramate Manoonpong
Abstract    Full text HTML    Full text PDF

4. EANN 2012: exploratory analysis of mobile phone traffic patterns using 1-dimensional SOM, clustering and anomaly detection
Author(s): Pekka Kumpulainen & Kimmo Hätönen
Abstract    Full text HTML    Full text PDF

5. Neural Adaptive Control in Application Service Management Environment
Author(s): Tomasz D. Sikora & George D. Magoulas
Abstract    Full text HTML    Full text PDF

Reminder: paper submission deadline for SCDM 2014

A reminder that the deadline for submitting papers to the First International Conference on Data Mining (SCDM) 2014 is 15 December 2014. This conference will be held in Kuala Lumpur, Malaysia, 16-18 June, 2014.

Call for papers: Special Session for WCCI 2014 "Applications of Computational lntelligence in Ecological Informatics and Environmental Modelling"

Aim

The aim of this special session is to provide a forum for recent research in the application of computational intelligence in the areas of ecological informatics, ecological modelling and environmental modelling.

Ecological informatics and the related field of ecological modelling involve constructing computational models of ecological systems. These models include such things as the distribution or abundance of particular species, models of the interaction between multiple species, and models of the future development of populations. Environmental modelling is closely related and involves constructing models of the physical environment that biological eco-systems inhabit. These models cover such topics as the climate and climate change and the detection of landscape features from geographical data. Models have also been constructed of such environmental topics as waste management systems, water quality and drainage systems and air pollution. As these are highly-complex systems, algorithms from the field of computational intelligence have already been widely applied to modelling this data. Previous work has successfully applied artificial neural networks, fuzzy systems, evolutionary algorithms, support vector machines and combinations of these including neuro-fuzzy and neuro-evolutionary approaches. In each case, computational intelligence methods were shown to be more effective at solving the problem than the alternative methods.

Scope

Topics relevant to this special session include, but are not limited to, the following applications of computational intelligence, including Artificial Neural Networks, Fuzzy Systems, and Evolutionary Algorithms:

•    Species distribution and ecological niche modelling
•    Predicting species abundance
•    Remote sensing image analysis and content-based image retrieval for Ecological Informatics and Environmental Modelling
•    Analysis of species assemblages
•    Issues in the preparation of ecological data for modelling
•    Modelling of pollutants in air, land or water
•    Modelling water quality
•    Predicting the effects of climate change
•    Predicting crop hazards, pests or diseases
•    Identifying landscape features
•    Modelling ecosystem biomass

Deadline

The deadline for submissions to this special session is 20 December 2013.

Information for Authors

1)    Information on the format and templates for papers can be found here:
       http://www.ieee-wcci2014.org/Paper%20Submission.htm
2)    Papers should be submitted via the IJCNN 2014 paper submission site:
       http://ieee-cis.org/conferences/ijcnn2014/upload.php3) 
       Select the Special Session name in the Main Research topic dropdown list
4)    Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of December 20, 2013

Organisers

•    Dr Michael J Watts, AIS St Helens, Auckland, New Zealand. mjwatts@ieee.org
•    Associate Professor Russel Pears, Auckland University of Technology, Auckland, New Zealand, russel.pears@aut.ac.nz
•    Professor Jie Yang, Shanghai Jiao Tong University, Shanghai, China, jieyang@sjtu.edu.cn

IEEE Transactions on Fuzzy Systems: Volume 21, Issue 5, October 2013

1. Fuzzy-Model-Based Fault-Tolerant Design for Nonlinear Stochastic Systems Against Simultaneous Sensor and Actuator Faults
Author(s): Ming Liu ; Xibin Cao ; Peng Shi
Page(s): 789-799

2. Stability Analysis of Polynomial-Fuzzy-Model-Based Control Systems Using Switching Polynomial Lyapunov Function
Author(s): Lam, H.K. ; Narimani, M. ; Hongyi Li ; Honghai Liu
Page(s): 800-813

3. Hierarchical Clustering Problems and Analysis of Fuzzy Proximity Relation on Granular Space
Author(s): Xu-Qing Tang ; Ping Zhu
Page(s): 814-824

4. RFRR: Robust Fuzzy Rough Reduction
Author(s): Suyun Zhao ; Hong Chen ; Cuiping Li ; Mengyao Zhai ; Xiaoyong Du
Page(s): 825-841

5. Model Checking of Linear-Time Properties Based on Possibility Measure
Author(s): Yongming Li ; Lijun Li
Page(s): 842-854

6. Clustering Spatiotemporal Data: An Augmented Fuzzy C-Means
Author(s): Izakian, H. ; Pedrycz, W. ; Jamal, I.
Page(s): 855-868

7. Conditional Density Estimation Using Probabilistic Fuzzy Systems
Author(s): van den Berg, J. ; Kaymak, U. ; Almeida, R.J.
Page(s): 869-882

8. Robust Stability and Stabilization of Uncertain T–S Fuzzy Systems With Time-Varying Delay: An Input–Output Approach
Author(s): Lin Zhao ; Huijun Gao ; Karimi, H.R.
Page(s): 883-897

9. Multiary α-Resolution Principle for a Lattice-Valued Logic
Author(s): Yang Xu ; Jun Liu ; Xiaomei Zhong ; Shuwei Chen
Page(s): 898-912

10. Adaptive Fuzzy Decentralized Output Feedback Control for Nonlinear Large-Scale Systems With Unknown Dead-Zone Inputs
Author(s): Shaocheng Tong ; Yongming Li
Page(s): 913-925

11. Chaos-Based Fuzzy Regression Approach to Modeling Customer Satisfaction for Product Design
Author(s): Huimin Jiang ; Kwong, C.K. ; Ip, W.H. ; Zengqiang Chen
Page(s): 926-936

12. Induction of Shadowed Sets Based on the Gradual Grade of Fuzziness
Author(s): Tahayori, H. ; Sadeghian, A. ; Pedrycz, W.
Page(s): 937-949

13. A Genetic Fuzzy Linguistic Combination Method for Fuzzy Rule-Based Multiclassifiers
Author(s): Trawinski, K. ; Cordon, O. ; Sanchez, L. ; Quirin, A.
Page(s): 950-965

14. Network-Based Robust Passive Control for Fuzzy Systems With Randomly Occurring Uncertainties
Author(s): Zheng-Guang Wu ; Peng Shi ; Hongye Su ; Jian Chu
Page(s): 966-970

15. A Simple Fuzzy Method to Remove Mixed Gaussian-Impulsive Noise From Color Images
Author(s): Camarena, J.-G. ; Gregori, V. ; Morillas, S. ; Sapena, A.
Page(s): 971-977

16. Proximity-Based Clustering: A Search for Structural Consistency in Data With Semantic Blocks of Features
Author(s): Pedrycz, W.
Page(s): 978-982

17. A Note on Fuzzy Relational Equations With Min-Implication Composition
Author(s): Pingke Li
Page(s): 983-986

18. Comments on “Quantized Control Design for Impulsive Fuzzy Networked Systems”
Author(s): Guotao Hui ; Jun Yang ; Bonan Huang
Page(s): 987

IEEE Transactions on Neural Networks and Learning Systems: Volume 24, Issue 11, November 2013

1. Error Surface of Recurrent Neural Networks
Author(s): Phan, M.C. ; Hagan, M.T.
Pages: 1709-1721
 
2. Single-Channel Blind Separation Using Pseudo-Stereo Mixture and Complex 2-D Histogram
Author(s): Tengtrairat, N. ; Gao, B. ; Woo, W.L. ; Dlay, S.S.
Pages:  1722-1735

3. On the SVMpath Singularity
Author(s): Dai, J. ; Chang, C. ; Mai, F. ; Zhao, D. ; Xu, W.
Pages: 1736-1748
 
4. Multistability of Two Kinds of Recurrent Neural Networks With Activation Functions Symmetrical About the Origin on the Phase Plane
Author(s): Zeng, Z. ; Zheng, W.X.
Pages: 1749-1762
 
5. Safety-Aware Semi-Supervised Classification
Author(s): Wang, Y. ; Chen, S.
Pages: 1763-1772

6. Neural Network Approaches for Noisy Language Modeling
Author(s): Li, J. ; Ouazzane, K. ; Kazemian, H.B. ; Afzal, M.S.
Pages: 1773-1784

7. A New Discrete-Continuous Algorithm for Radial Basis Function Networks Construction
Author(s): Zhang, L. ; Li, K. ; He, H. ; Irwin, G.W.
Pages: 1785-1798

8. Finding Potential Support Vectors in Separable Classification Problems
Author(s): Varagnolo, D. ; Del Favero, S. ; Dinuzzo, F. ; Schenato, L. ; Pillonetto, G.
Pages: 1799-1813

9. Nonlinear Systems Identification and Control Via Dynamic Multitime Scales Neural Networks
Author(s): Fu, Z.-J. ; Xie, W.-F. ; Han, X. ; Luo, W.-D.
Pages: 1814-1823

10. Hierarchical Similarity Transformations Between Gaussian Mixtures
Author(s): Rigas, G. ; Nikou, C. ; Goletsis, Y. ; Fotiadis, D.I.
Pages: 1824-1835

11. Negative Correlation Ensemble Learning for Ordinal Regression
Author(s): Fernandez-Navarro, F. ; Gutierrez, P.A. ; Hervas-Martinez, C. ; Yao, X.
Pages: 1836-1849

12. Online Learning of a Dirichlet Process Mixture of Beta-Liouville Distributions Via Variational Inference
Author(s): Fan, W. ; Bouguila, N.
Pages: 1850-1862

13. Transfer Ordinal Label Learning
Author(s): Seah, C.-W. ; Tsang, I.W. ; Ong, Y.-S.
Pages: 1863-1876

14. Pseudo-Orthogonalization of Memory Patterns for Associative Memory
Author(s): Oku, M. ; Makino, T. ; Aihara, K.
Pages: 1877-1887

15. Multilabel Classification Using Error-Correcting Codes of Hard or Soft Bits
Author(s): Ferng, C.-S. ; Lin, H.-T.
Pages: 1888-1900

16. Multiclass Support Vector Machines With Example-Dependent Costs Applied to Plankton Biomass Estimation
Author(s): Gonzalez, P. ; Alvarez, E. ; Barranquero, J. ; Diez, J. ; Gonzalez-Quiros, R. ; Nogueira, E. ; Lopez-Urrutia, A. ; del Coz, J.J.
Pages: 1901-1905

17. Corrections to: “Estimator Design for Discrete-Time Switched Neural Networks With Asynchronous Switching and Time-Varying Delay”
Author(s): Zhang, D. ; Yu, L. ; Wang, Q.-G. ; Ong, C.
Pages:  1906

Prioritizing insect pests with Kohonen SOM

My research interests and activities are split between two fields: computational intelligence (obviously) and ecological modelling. Although I got into ecological modelling via computational intelligence, many of my recent publications in ecological modelling haven't had anything to do with computational intelligence. An exception to this is a recently published paper in the journal Neobiota that I am a coauthor of: "Prioritizing the risk of plant pests by clustering methods: self-organising maps, k-means and hierarchical clustering".

The problem is this: given the species that are known to exist in various geo-political regions of the world, what is the likelihood of one of those species establishing in a region where it is not already present? Species presences and absences are represented by binary vectors, where each region has a vector, a one represents a presence of a particular species in that region, and a zero represents an absence in that region. By clustering the assemblage vectors using a SOM, it is possible to infer which species pose the greatest threat to any particular region.

The rationale behind this approach is that regions that have similar species assemblages are likely to have similar environments. So if several assemblages end up in the same cluster, and a species is present in many of those regions but absent in others, then that species is likely to become established in the regions from which it is absent.

In this work the SOM were used as data clustering algorithms, with the vector quantisation abilities of the SOM being largely underutilized. My own contribution to the work was the realisation that the SOM were being used to cluster data, and hence to test the approach against the much-faster k-means clustering algorithm. I found that k-means is just as effective at producing good clusters as the SOM, and is much faster.

There are some problems with this work as well: it is virtually impossible to determine which approach is better without testing data. Which means that if you are clustering a set of species assemblages, you also need some more up-to-date data to validate the predictions. I do have some thoughts on getting around this, which I am currently investigating.

Call for papers: Special Session for WCCI 2014 "Applications of Computational lntelligence in Ecological Informatics and Environmental Modelling"

Aim

The aim of this special session is to provide a forum for recent research in the application of computational intelligence in the areas of ecological informatics, ecological modelling and environmental modelling.

Ecological informatics and the related field of ecological modelling involve constructing computational models of ecological systems. These models include such things as the distribution or abundance of particular species, models of the interaction between multiple species, and models of the future development of populations. Environmental modelling is closely related and involves constructing models of the physical environment that biological eco-systems inhabit. These models cover such topics as the climate and climate change and the detection of landscape features from geographical data. Models have also been constructed of such environmental topics as waste management systems, water quality and drainage systems and air pollution. As these are highly-complex systems, algorithms from the field of computational intelligence have already been widely applied to modelling this data. Previous work has successfully applied artificial neural networks, fuzzy systems, evolutionary algorithms, support vector machines and combinations of these including neuro-fuzzy and neuro-evolutionary approaches. In each case, computational intelligence methods were shown to be more effective at solving the problem than the alternative methods.

Scope

Topics relevant to this special session include, but are not limited to, the following applications of computational intelligence, including Artificial Neural Networks, Fuzzy Systems, and Evolutionary Algorithms:

•    Species distribution and ecological niche modelling
•    Predicting species abundance
•    Remote sensing image analysis and content-based image retrieval for Ecological Informatics and Environmental Modelling
•    Analysis of species assemblages
•    Issues in the preparation of ecological data for modelling
•    Modelling of pollutants in air, land or water
•    Modelling water quality
•    Predicting the effects of climate change
•    Predicting crop hazards, pests or diseases
•    Identifying landscape features
•    Modelling ecosystem biomass

Deadline

The deadline for submissions to this special session is 20 December 2013.

Information for Authors

1)    Information on the format and templates for papers can be found here:
       http://www.ieee-wcci2014.org/Paper%20Submission.htm
2)    Papers should be submitted via the IJCNN 2014 paper submission site:
       http://ieee-cis.org/conferences/ijcnn2014/upload.php3) 
       Select the Special Session name in the Main Research topic dropdown list
4)    Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of December 20, 2013

Organisers

•    Dr Michael J Watts, AIS St Helens, Auckland, New Zealand. mjwatts@ieee.org
•    Associate Professor Russel Pears, Auckland University of Technology, Auckland, New Zealand, russel.pears@aut.ac.nz
•    Professor Jie Yang, Shanghai Jiao Tong University, Shanghai, China, jieyang@sjtu.edu.cn

Conference paper deadline: KES 2014

The deadline for submitting papers to the 18th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES) 2014 is 15 March, 2014. This conference will be held in Gdynia, Poland, 15-17 September, 2014.

Conference paper deadline: EAIS 2014

The deadline for submitting papers to the IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) 2014 is January 15, 2014. This conference will be held in Linz, Austria, June 2-4, 2014.

Reminder: paper submission deadline: ICAISC 2014

A reminder that the deadline for submitting papers to the 13th International Conference on Artificial Intelligence and Soft Computing (ICAISC) 2014 is November 20, 2013 (beware the front page linked to has embedded folk-music playing). This conference will be held in Zakopane, Poland, June 1-5 2014.

Video: How to publish your research in IEEE CIS publications

A panel discussion on how to publish in the IEEE Computational Intelligence Society's publications. This discussion wraps up the individual talks by Professors Xin Yao, Kay Chen Tan, Derong Liu, Garrison Greenwood, Chin-Teng Lin and Simon M. Lucas . This panel session was part of the CEC 2013 conference.

How to publish your research: Video of Professor Simon M. Lucas

Professor Simon M. Lucas talks about how to publish research in IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games. This talk was part of a panel session at CEC 2013 and mostly talks about what kind of papers are published in TCIAIG.

How to publish your research: Video of Professor Chin-Teng Lin

Professor Chin-Teng Lin, who is the editor-in-chief of IEEE Transactions on Fuzzy Systems, speaks about publishing in that journal. This talk was part of a panel discussion at the CEC 2013 conference. Some of the points he makes in this talk are applicable to publishing in most journals:

• Read existing papers, know the field
• Present an issue of significance
• Choose a journal that fits well with your research
• Use the correct format for that journal
• Have focus & vision, don't be too ambitious with your paper
• Write clearly
• Get pre-review, ask  your colleagues to check your paper before submission
• Proofread!
• Be patient, reviews take time

How to publish your research: Video of Professor Garrison Greenwood

Professor Garrison Greenwood talks about how to publish your research in the IEEE Transactions on Evolutionary Computation. This talk was part of a panel session at the CEC 2013 conference.

The main points of this talk are:

• Establish the context of your research in the Related Research section following the introduction (as a side-note, in other fields this is the introduction: why does computer science insist of separating them?

• Use enough citations, and no more

• Write enough detail for a competent researcher to replicate your work, don't try to write a tutorial

• Read the instructions for authors

• Use good grammar and spelling

How to publish your research: Video of Professor Derong Liu

Professor Derong Liu talks about how to publish your research in IEEE Transactions on Neural Networks and Learning Systems at a panel session at the CEC 2013 conference. This talk gives a lot of information about the editorial and review process, as well as how to increase your chances of having a paper accepted and even how to get on the editorial board of the journal.