Soft Computing

Course Objectives :

1. To learn the basic concepts of Soft Computing
2. To introduce the concepts of fuzzy sets and fuzzy logic
3. To make students familiar with genetic algorithms, its applications and advances
4. To make students familiar with neural networks that can learn from available examples

Course Outcomes (CO)

1. CO 1 - Comprehend soft computing techniques and its applications.
2. CO 2 - Understand the artificial neural networks and its applications
3. CO 3 - Analyse the single-objective optimization problems using GAs
4. CO 4 - Develop the fuzzy logic sets and membership function and defuzzification techniques.

UNIT-I

Introduction to Soft Computing: Concept of computing systems, "Soft" computing versus "Hard" computing, Characteristics of Soft computing, Some applications of Soft computing techniques

UNIT-II

Fuzzy logic: Introduction to Fuzzy logic, Fuzzy sets and membership functions, Operations on Fuzzy sets, Fuzzy relations, rules, propositions, implications and inferences, Defuzzification techniques, Some applications of Fuzzy logic.

UNIT-III

Genetic Algorithms: Concept of "Genetics" and "Evolution" and its application to probabilistic search techniques, Basic GA framework and different GA architectures, GA operators: Encoding, Crossover, Selection, Mutation, etc. Solving single-objective optimization problems using GAs.

UNIT - IV

Artificial Neural Networks: Biological neurons and its working, Simulation of biological neurons to problem solving, Different ANNs architectures, Training techniques for ANNs, Applications of ANNs to solve some real-life problems. Fuzzy Neural systems, Genetic Fuzzy systems, Genetic Neural system

Textbook(s):

1. J.S.R.Jang, C.T.Sun and E.Mizutani, “Neuro-Fuzzy and Soft Computing”, PHI, 2004
2. S.N.Sivanandam & S.N.Deepa “Principles of Soft Computing” Wiley India Pvt. Ltd., 2007

References:

1. S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2003.
2. Timothy J.Ross, “Fuzzy Logic with Engineering Applications”, McGraw-Hill, 1997