MC9296 SOFT COMPUTING Syllabus for 5th Sem MCA - Fifth semester - Regulation 2009 - Anna University


MC9296                                      SOFT COMPUTING                                             LT P C
3 0 0 3


UNIT I           INTRODUCTION TO SOFT COMPUTING AND NEURAL NETWORK 9
Evolution  of  Computing  -  Soft  Computing  Constituents   From  Conventional  AI  to
Computational Intelligence - Machine Learning Basics

UNIT II            GENETIC ALGORITHMS                                                                         9
Introduction to Genetic Algorithms (GA) – Applications of GA in Machine Learning - Machine Learning Approach to Knowledge Acquisition.

UNIT III           NEURAL NETWORKS                                                                              9
Machine Learning Using Neural Network, Adaptive Networks Feed forward Networks Supervised  Learning  NeuraNetworks   RadiaBasis  Function  Networks  - Reinforcement Learning Unsupervised Learning Neural Networks – Adaptive Resonance architectures Advances in Neural networks.

UNIT IV          FUZZY LOGIC                                                                                           9
Fuzzy Sets Operations on Fuzzy Sets Fuzzy Relations Membership Functions- Fuzzy Rules and Fuzzy Reasoning Fuzzy Inference Systems  Fuzzy Expert Systems
Fuzzy Decision Making.

UNIT V           NEURO-FUZZY MODELING                                                                    9
Adaptive Neuro-Fuzzy Inference Systems Coactive Neuro-Fuzzy Modeling Classification and Regression Trees Data Clustering Algorithms – Rulebase Structure Identification Neuro-Fuzzy Control Case studies.

TOTAL : 45 PERIODS

TEXT BOOKS:
1.  Jyh-Shing  Roger  Jang,  Chuen-Tsai  Sun,  Eiji  Mizutani,  “Neuro-Fuzzy  and  Soft
Computing, Prentice-Hall of India, 2003.
2.  Georg J.   Kli an B Yuan Fuzzy   Set an Fuzzy   Logic-Theor and
Applications,Prentice Hall, 1995.
3.  Jame A Freema an Davi M Skapura “Neura Networks   Algorithms, Applications, and Programming Techniques, Pearson Edn., 2003.


REFERENCES:
1.  Mitchell Melanie, An Introduction to Genetic Algorithm”, Prentice Hall, 1998.
2.  David  E.  Goldberg,  Genetic  Algorithms  in  Search,  Optimization  and  Machine
Learning, Addison Wesley, 1997.
3.  S. N. Sivanandam, S. Sumathi and S. N. Deepa, Introduction to Fuzzy Logic using
MATLAB, Springer, 2007.
4.  S.N.Sivanandam · S.N.Deepa, Introduction to Genetic Algorithms, Springer, 2007.
5.  Jacek M. Zurada, Introduction to Artificial Neural Systems, PWS Publishers, 1992.
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