CS2053 SOFT COMPUTING

CS2053 SOFT COMPUTING L T P C

3 0 0 3

UNIT I FUZZY SET THEORY 10

Introduction to Neuro – Fuzzy and Soft Computing – Fuzzy Sets – Basic Definition and

Terminology – Set-theoretic Operations – Member Function Formulation and

Parameterization – Fuzzy Rules and Fuzzy Reasoning – Extension Principle and Fuzzy

Relations – Fuzzy If-Then Rules – Fuzzy Reasoning – Fuzzy Inference Systems –

Mamdani Fuzzy Models – Sugeno Fuzzy Models – Tsukamoto Fuzzy Models – Input

Space Partitioning and Fuzzy Modeling.

UNIT II OPTIMIZATION 8

Derivative-based Optimization – Descent Methods – The Method of Steepest Descent –

Classical Newton’s Method – Step Size Determination – Derivative-free Optimization –

Genetic Algorithms – Simulated Annealing – Random Search – Downhill Simplex

Search.

UNIT III ARTIFICIAL INTELLIGENCE 10

Introduction, Knowledge Representation – Reasoning, Issues and Acquisition:

Prepositional and Predicate Calculus Rule Based knowledge Representation Symbolic

Reasoning Under Uncertainity Basic knowledge Representation Issues Knowledge

acquisition – Heuristic Search: Techniques for Heuristic search Heuristic Classification -

State Space Search: Strategies Implementation of Graph Search Search based on

Recursion Patent-directed Search Production System and Learning.

UNIT IV NEURO FUZZY MODELING 9

Adaptive Neuro-Fuzzy Inference Systems – Architecture – Hybrid Learning Algorithm –

Learning Methods that Cross-fertilize ANFIS and RBFN – Coactive Neuro Fuzzy

Modeling – Framework Neuron Functions for Adaptive Networks – Neuro Fuzzy

Spectrum.

UNIT V APPLICATIONS OF COMPUTATIONAL INTELLIGENCE 8

Printed Character Recognition – Inverse Kinematics Problems – Automobile Fuel

Efficiency Prediction – Soft Computing for Color Recipe Prediction.

TOTAL= 45 PERIODS

TEXT BOOKS:

1. J.S.R.Jang, C.T.Sun and E.Mizutani, “Neuro-Fuzzy and Soft Computing”, PHI, 2004,

Pearson Education 2004.

2. N.P.Padhy, “Artificial Intelligence and Intelligent Systems”, Oxford University Press,

2006.

REFERENCES:

1. Elaine Rich & Kevin Knight, Artificial Intelligence, Second Edition, Tata Mcgraw Hill

Publishing Comp., 2006, New Delhi.

2. Timothy J.Ross, “Fuzzy Logic with Engineering Applications”, McGraw-Hill, 1997.

3. Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”,

Addison Wesley, N.Y., 1989.

4. S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic

Algorithms”, PHI, 2003.

5. R.Eberhart, P.Simpson and R.Dobbins, “Computational Intelligence - PC Tools”, AP

Professional, Boston, 1996.

6. Amit Konar, “Artificial Intelligence and Soft Computing Behaviour and Cognitive model

of the human brain”, CRC Press, 2008.