Soft Computing
Dear Student on this page you can find my lecture notes for your guideline. These slides you can download for your study purpose. But I will suggest you plz follow the books also to enhance your knowledge because these notes are not sufficient. These notes are only for guideline and understaning purpose.
Books for Soft Computing that you can follow.
M. Mitchell: An Introduction to Genetic Algorithms, Prentice-Hall.
J.S.R.Jang, C.T.Sun and E.Mizutani: Neuro-Fuzzy and Soft Computing, PHI, Pearson Education.
Timothy J.Ross: Fuzzy Logic with Engineering Applications, McGraw-Hill.
Davis E.Goldberg: Genetic Algorithms: Search, Optimization and Machine Learning, Addison
Wesley.
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5. S. Rajasekaran and G.A.V.Pai: Neural Networks, Fuzzy Logic and Genetic Algorithms, PHI.
6. D. E. Goldberg: Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-
Wesley.
7. Z. Michalewicz: Genetic Algorithms+ Data Structures = Evolution Programs, Springer-Verlag.
8. N.K. Sinha & M. M. Gupta(Eds): Soft Computing & Intelligent Systems: Theory & Applications,
Academic Press.
9. M.T. Hagan, H. B. Demuth, And M. Beale: Neural Network Design, Thompson Learning.
10. C. Lau (Ed): Neural Networks, IEEE Press.
11. J. Freeman and D. Skapura: Neural Networks: Algorithms, Applications, and Programming
Techniques, Addison-Wesley.
12. G. J. Klir and T. A. Folger: Fuzzy Sets, Uncertainty, and Information, PHI.
13. A. Konar: Computational Intelligence Principles, Techniques and Applications, Springer.
14. Kishan Mehrotra, Chilukuri K. Mohan and Sanjay Ranka: Elements of Artificial Neural
Networks, Penram, Mumbai.
15. J.S.R. Jang, C.T. Sun, E. Mizutani: Neuro-Fuzzy and Soft Computing: A Computational
Approach to Learning and Machine Intelligence, Prentice Hall.
16. Mitchell, Melanie: An Introduction to Genetic Algorithms, PHI.
17. David E Goldberg: Genetic Algorithms in Search, Optimization & Machine Learning, Addison
Wesley.