New frontiers in computational intelligence and its applications

This three-volume set brings together 202 accepted research papers from CIMCA '99. The goal of this conference was to exchange ideas between theoreticians and practitioners, and address the various issues in computational modelling, control and automation. Volume one is dedicated to the theory and applications of neural networks and advanced intelligent control systems for manufacturing, robotics and automation. Volume two covers the theory and applications of evolutionary computation and fuzzy logic for intelligent control, knowledge acquisition and information retrieval. Finally, volume three encompasses computational techniques for intelligent image processing, data analysis and information retrieval.

[1]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[2]  Chuen-Tsai Sun,et al.  Rule-base structure identification in an adaptive-network-based fuzzy inference system , 1994, IEEE Trans. Fuzzy Syst..

[3]  P. K. Simpson.  Fuzzy Min-Max Neural Networks-Part 1 : Classification , 1992 .

[4]  Witold Pedrycz,et al.  Fuzzy sets in pattern recognition: Methodology and methods , 1990, Pattern Recognit..

[5]  Chin-Teng Lin,et al.  Neural-Network-Based Fuzzy Logic Control and Decision System , 1991, IEEE Trans. Computers.

[6]  Hisao Ishibuchi,et al.  Adaptive fuzzy rule-based classification systems , 1996, IEEE Trans. Fuzzy Syst..

[7]  Donald Gustafson,et al.  Fuzzy clustering with a fuzzy covariance matrix , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

[8]  James M. Keller,et al.  A possibilistic approach to clustering , 1993, IEEE Trans. Fuzzy Syst..

[9]  Patrick K. Simpson,et al.  Fuzzy min-max neural networks - Part 2: Clustering , 1993, IEEE Trans. Fuzzy Syst..