Title :
On the optimization of fuzzy systems using bio-inspired strategies
Author :
De Oliveira, J. Valente
Author_Institution :
Dept. of Math. & Comput. Sci., UBI, Covilha, Portugal
Abstract :
The optimization of fuzzy systems using bio-inspired strategies, such as neural network learning rules or evolutionary optimization techniques, is becoming more and more popular. In general, fuzzy systems optimized in such a way cannot provide a linguistic interpretation, preventing us from using one of their most interesting and useful features. This work addresses this difficulty and present a design methodology to overcome it. A set of properties that obviate the subjective task of interpreting linguistically fuzzy systems is provided. These properties are translated in terms of nonlinear constraints that are coded within a given optimization scheme, such as backpropagation. Illustrative numerical examples are also included
Keywords :
backpropagation; computational linguistics; fuzzy set theory; fuzzy systems; genetic algorithms; neural nets; backpropagation; evolutionary optimization; fuzzy systems; genetic algorithm; learning rules; linguistic modelling; membership functions; neural network; optimization; semantics; Biological control systems; Biological system modeling; Computer science; Constraint optimization; Design methodology; Fuzzy sets; Fuzzy systems; Genetic algorithms; Mathematics; Neural networks;
Conference_Titel :
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4863-X
DOI :
10.1109/FUZZY.1998.686294
