Computational Intelligence in Control

• #1. Designing Neural Network Ensembles by Minimizing Mutual Information
• #2. A Perturbation Size-Independent Analysis of Robustness in Neural Networks by Randomized Algorithms
• #3. Helicopter Motion Control Using a General Regression Neural Network
• #4. A Biologically Inspired Neural Network Approach to Real-Time Map Building and Path Planning
• #5. Evolutionary Learning of Fuzzy Control in Robot-Soccer
• #6. Evolutionary Learning of a Box-Pushing Controller
• #7. Computational Intelligence for Modelling and Control of Multi-Robot Systems
• #8. Integrating Genetic Algorithms and the Finite Element Analysis for Structural Inverse Problems
• #9. On the Modelling of a Human Pilot Using Fuzzy Logic Control
• #10. Bayesian Agencies in Control
• #11. Simulation Model for the Control of Olive Fly Bactrocera Oleae Using Artificial Life Technique
• #12. Applications of Data-Driven Modelling and Machine Learning in Control of Water Resources
• #13. Solving Two Multi-Objective Optimization Problems Using Evolutionary Algorithm
• #14. Flexible Job-Shop Scheduling Problems: Formulation, Lower Bounds, Encoding and Controlled Evolutionary Approach
• #15. The Effect of Multi-Parent Recombination on Evolution Strategies for Noisy Objective Functions
• #16. On Measuring the Attributes of Evolutionary Algorithms: A Comparison of Algorithms Used for Information Retrieval
• #17. Design Wind Speeds Using Fast Fourier Transform: A Case Study

Masoud Mohammadian has completed his Bachelor, Master and PhD in Computer Science. His research interests lie in adaptive self-learning systems, fuzzy logic, genetic algorithms, neural networks and their applications in robotics, control, industrial automation, financial and business problems which involve real time data processing, planning and decision making. He is a member of over 30 international conferences and he has chaired several international conferences in computational intelligence and intelligent agents. He is currently a senior lecturer at the school of computing at the University of Canberra in Australia. He is a member of many professional (computing and engineering) organizations . He is also currently the vice chair of the Institute of Electrical and Electronic Engineering (IEEE) ACT section.

Ruhul Sarker received his PhD in 1991 from DalTech, Dalhousie University, Halifax, Canada, and is currently a senior lecturer in Operations Research at the School of Computer Science, University of New South Wales, ADFA Campus, Canberra, Australia. Before joining at UNSW in February 1998, Dr. Sarker worked with Monash University, Victoria, and the Bangladesh University of Engineering and Technology, Dhaka. His main research interests are Evolutionary Optimization, Data Mining and Applied Operations Research. He was involved with three edited books either as editor or co-editor, and has published more than 80 refereed papers in international journals and conference proceedings. He is also the editor of ASOR Bulletin, the national publication of the Australian Society for Operations Research.

Xin Yao received the BSc degree in computer science from the University of Science and Technology of China (USTC), Hefei, the MSc degree in computer science from the North China Institute of Computing Technologies (NCI), Beijing, and the PhD degree in computer science from the USTC, Hefei, in 1982, 1985, and 1990, respectively. He is currently a professor of computer science at the University of Birmingham, Birmingham, England. Xin Yao is an associate editor or a member of the editorial board of six international journals, including IEEE Transactions on Evolutionary Computation, and an editor/co-editor of nine journal special issues. His major research interests include combinations between neural and evolutionary computation techniques, evolutionary learning, co-evolution, evolutionary design and evolvable hardware, neural network ensembles, global optimization, simulated annealing, computational time complexity and data mining.