JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives:

• Familiarize with soft computing concepts
• Introduce and use the idea of fuzzy logic and use of heuristics based on human experience
• Familiarize the Neuro-Fuzzy modeling using Classification and Clustering techniques
• Learn the concepts of Genetic algorithm and its applications
• Acquire the knowledge of Rough Sets.

Course Outcomes

On completion of this course, the students will be able to:

• Identify the difference between Conventional Artificial Intelligence to Computational Intelligence.
• Understand fuzzy logic and reasoning to handle and solve engineering problems
• Apply the Classification and clustering techniques on various applications.
• Understand the advanced neural networks and its applications
• Perform various operations of genetic algorithms, Rough Sets.
• Comprehend various techniques to build model for various applications

UNIT - I

Introduction to Soft Computing: Evolutionary Computing, "Soft" computing versus "Hard" computing, Soft Computing Methods, Recent Trends in Soft Computing, Characteristics of Soft computing, Applications of Soft Computing Techniques.

UNIT - II

Fuzzy Systems: Fuzzy Sets, Fuzzy Relations, Fuzzy Logic, Fuzzy Rule-Based Systems

UNIT - III

Fuzzy Decision Making, Particle Swarm Optimization

UNIT - IV

Genetic Algorithms: Basic Concepts, Basic Operators for Genetic Algorithms, Crossover and Mutation Properties, Genetic Algorithm Cycle, Fitness Function, Applications of Genetic Algorithm.

UNIT - V

Rough Sets, Rough Sets, Rule Induction, and Discernibility Matrix, Integration of Soft Computing Techniques.

TEXT BOOK:

• 1. Soft Computing – Advances and Applications - Jan 2015 by B.K. Tripathy and J. Anuradha – Cengage Learning

REFERENCE BOOKS:

• 1. S. N. Sivanandam & S. N. Deepa, “Principles of Soft Computing”, 2nd edition, Wiley India, 2008.
• 2. David E. Goldberg, “Genetic Algorithms-In Search, optimization and Machine learning”, Pearson Education.
• 3. J. S. R. Jang, C.T. Sun and E.Mizutani, “Neuro-Fuzzy and Soft Computing”, Pearson Education, 2004.
• 4. G.J. Klir & B. Yuan, “Fuzzy Sets & Fuzzy Logic”, PHI, 1995.
• 5. Melanie Mitchell, “An Introduction to Genetic Algorithm”, PHI, 1998.
• 6. Timothy J. Ross, “Fuzzy Logic with Engineering Applications”, McGraw- Hill International editions, 1995