JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Prerequisite

Power System Analysis

Course Objectives

to prepare students to

• Understand fuzzy logic, artificial neural network (ANN)
• Understand genetic algorithm (GA) & evolutionary programming (EP)

Course Outcomes

Students will be able to

• Learn the concepts of biological foundations of artificial neural networks
• Learn Feedback networks and radial basis function networks and fuzzy logics
• Identifications of fuzzy and neural network
• Acquire the knowledge of GA

UNIT - I

Biological foundations to intelligent Systems, Artificial Neural Networks, Single layer and Multilayer Feed Forward NN, LMS and Back Propagation Algorithm, Feedback networks and Radial Basis Function Networks.

UNIT - II

Fuzzy Logic, Knowledge Representation and Inference Mechanism, Defuzzification Methods. Fuzzy Neural Networks and their learning methods

UNIT - III

System Identification using Fuzzy and Neural Network.

UNIT - IV

Genetic algorithm, Reproduction cross over, mutation, Introduction to evolutionary program.

UNIT - V

Applications of above mentioned techniques to practical problems on power engineering

TEXT BOOKS:

• 1. J M Zurada , “An Introduction to ANN”, Jaico Publishing House
• 2. Simon Haykins, “Neural Networks”, Prentice Hall

REFERENCES:

• 1. Timothy Ross, “Fuzzy Logic with Engg.Applications”, McGraw. Hill
• 2. Driankov, Dimitra, “An Introduction to Fuzzy Control”, Narosa Publication
• 3. Golding, “Genetic Algorithms”, Addison-Wesley Publishing Co.
• 4. NPTEL Course on “Introduction to Soft Computing” by Prof. Debasis Samanta, https://www.youtube.com/playlist?list=PLJ5C_6qdAvBFqAYS0P9INAogIMklG8E-9
• 5. NPTEL Course on Neural Networks and Applications, https://www.youtube.com/playlist?list=PL53BE265CE4A6C056 R19 M. TECH. EPE/EPS M. TECH. I Year II Sem. (EPE/EPS)