EE 7102 SOFT COMPUTING TECHNIQUES & APPLICATIONS Syllabus Electrical Engineering(EE) 7th sem RGTU/RGPV Syllabus
EE 7102 SOFT COMPUTING TECHNIQUES & APPLICATIONS Course Contents:
Review of probability theory: Random variable, distribution functions , function of random variable. generation of random digit, and random variants from various distribution function, Monte Carlo simulation, sampling distributions station evolution using MCS, confidence interval, coefficient of variation.
- rule, and back propagation rule of training, RBF and FLN network.
Draw back of classical optimization techniques, genetic algorithm; binary and real parameter GA, constraints handling in GA.
Evolution strategies(ES), two members non-recombinative ES, multi member ES, recombinative ES.
Optimization based on swarm intelligence particle, swarm optimization and its variants .
Application of soft computing techniques to problem of electrical engg. e.g. economic dispatch, reliable optimization, ANN training using evolutionary algorithms.
1. R.Y. Rubinstein Simulation and the Monte Carlo method, John Wiley &
sons 1st Edition.
2 Paul. L. Mayer-Introducing probability and statical application, Addition
3 Rajasekaran and pai- Neural Network, Fuzzy logic & Genetic Algorithms.
4 LiMin. Fu, Neural Networks in Computer Intelligence, 9th Reprint TMH
5 Multi objective optimization using evolutionary algorithm- Kalyanmoy Deb John
Wiley & Sons Ltd.
6 Probability and Random processes for Electrical Engineering , Alberto Leon Garcia IInd Pearson .
. 7 Principles of soft computing- S N Shivanandan, S N Deepa Wiley India (P) Ltd, I edition 2007.
8 Hand book of genetic algorithm- Rajaserkharans, vijaya laxmi pai.
9 PSO Tutorial- Kennedy Ebuehart.
10 Sivanandam & Deepa- An Introduction to Neural Networks using
Matlab 6.0 1st ed., TMH
11 M.Amirthavalli, Fuzzy logic and neural networks, Scitech publications.