AI TECHNIQUES IN ELECTRICAL ENGINEERING (SYLLABUS MTECH-EPS II SEM)

UNIT – I: ARTIFICIAL NEURAL NETWORKS
Introduction-Models of Neural Network - Architectures – Knowledge representation – Artificial
Intelligence and Neural networks–Learning process – Error correction learning – Hebbian
learning –Competitive learning –Boltzman learning –Supervised learning – Unsupervised learning
– Reinforcement learning- learning tasks.
UNIT- II: ANN PARADIGMS
Multi – layer perceptron using Back propagation Algorithm-Self – organizing Map – Radial Basis
Function Network – Functional link, network – Hopfield Network.
UNIT – III: FUZZY LOGIC
Introduction – Fuzzy versus crisp – Fuzzy sets - Membership function – Basic Fuzzy set
operations – Properties of Fuzzy sets – Fuzzy cartesion Product –Operations on Fuzzy relations
– Fuzzy logic – Fuzzy Quantifiers-Fuzzy Inference-Fuzzy Rule based system-Defuzzification
methods.
UNIT – IV: GENETIC ALGORITHMS
Introduction-Encoding –Fitness Function-Reproduction operators-Genetic Modeling –Genetic
operators-Crossover-Single – site crossover-Two point crossover –Multi point crossover-Uniform
crossover – Matrix crossover-Crossover Rate-Inversion & Deletion –Mutation operator –Mutation
–Mutation Rate-Bit-wise operators-Generational cycle-convergence of Genetic Algorithm.
UNIT–V: APPLICATIONS OF AI TECHNIQUES
Load forecasting – Load flow studies – Economic load dispatch – Load frequency control – Single
area system and two area system – Small Signal Stability (Dynamic stability) Reactive power
control – speed control of DC and AC Motors.
TEXT BOOK:
1. S.Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic & Genetic Algorithms”-
PHI, New Delhi, 2003.
REFERENCE BOOKS:
1. P.D.Wasserman,Van Nostrand Reinhold,”Neural Computing Theory & Practice”- New
York,1989.
2. Bart Kosko,”Neural Network & Fuzzy System” Prentice Hall, 1992.
3. G.J.Klir and T.A.Folger,”Fuzzy sets,Uncertainty and Information”-PHI, Pvt.Ltd,1994.
4. D.E.Goldberg,” Genetic Algorithms”- Addison Wesley 1999.