CE 31501: Soft Computing Tools in Engineering






Lecture Notes

Term Paper

Project Demo

Interesting Links










·         Dubois, D. and Prade, H. (1980), Fuzzy Sets and Systems - Theory and Applications, Academic Press, New York

·         Dayoff, J. E. (1990), Neural Networks architecture: An introduction, Van Nostrand Reinhold, New York

·         Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Publishing Company, Inc. Reading MA.

·         Recent research papers appearing in Journals such as AIEDM, Artificial Intelligence in Engineering, Expert Systems with applications, Neural Networks, Neural Computation. IEEE Journals etc.



Soft Computing

Author(s): D. K. Pratihar

ISBN:    978-81-7319-866-3 
Publication Year:   2007
Pages:   250  

About the book

This book starts with an introduction to soft computing, a family consisting of many members, namely Genetic Algorithms (GAs), Fuzzy Logic (FL), Neural Networks (NNs) and others. To realize the need for a non-traditional optimization tool like GA, one chapter is devoted to explain the principle of traditional optimization. The working cycle of a GA is explained in detail. The mechanisms of some specialized GAs are then discussed with appropriate examples. Fuzzy sets are introduced before explaining the principle of fuzzy reasoning and clustering. The fundamentals of NNs are presented, prior to the discussion on various forms of NN. The combined techniques, such as GA-FL, GA-NN, NN-FL and GA-FL-NN are explained in the last three chapters.



© 2014 Sudhirkumar Barai