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UNIT - I NEURAL NETWORKS AND ALGORITHMS OF NEURAL NETWORK

1.1 Neural Networks: Artificial Neural Network and Introduction

1.2 Learning Rules, Knowledge Representation and Acquisition

1.3 Different Methods of Learning

1.4 Algorithms of Neural Network: Feed-forward Error Back Propagation, Hopfield Model, Kohonen’s Featrure Map, K-Means Clustering, ART Networks, RBFN, Application of Neural Network to the relevant field

UNIT - II FUZZY LOGIC

2.1 Fuzzy Logic: Basic Concepts of Fuzzy Logic, Fuzzy vs Crisp Set, Linguistic variables, Membership Functions, Operations of Fuzzy Sets, Fuzzy If-Then Rules

2.2 Variable Inference Techniques, Defuzzification, Basic Fuzzy Inference Algorithm

2.3 Fuzzy System Design, FKBC and PID Control

2.4 Antilock Breaking System(ABS), Industrial Applications

UNIT - III OPTIMIZATION FUNDAMENTALS, LINEAR PROGRAMMING AND NON-LINEAR PROGRAMMING

3.1 Optimization Fundamentals: Definition, Classification of Optimization Problems

3.2 Unconstrained and Constrained Optimization, Optimality Conditions

3.3 LINEAR Programming: Simplex Method, Duality, Sensitivity Methods

3.4 NON-LINEAR Programming: Newton’s Method, GRG Method, Penalty Function Method, Augmented Langrange Multiplier Method, Dynamic Programming and Integer Programming

3.5 Interior Point Methods, Karmakar’s Algorithm, Dual Affine, Primal Affine

UNIT - IV GENETIC ALGORITHM

4.1 Genetic Algorithm: GA and Genetic Engineering, Finite Element based Optimization, PSO,BFO

4.2 Hybridization of Optimization Technique, Application of OptimizationTechnique for Solving Projects(Project solutions)

4.3 Implementation of Branch Relevant Industrial Applications by Matlab Code