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Engineering
GATE
School
Pharmacy
Competitive Exams
Intermediate
General
AI Techniques in Electrical Engineering
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Unit I: Artificial Neural Networks
9
Introduction
Models of Neuron 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
4
Multi-layer perceptron using Back propagation Algorithm (BPA)
Self –Organizing Map (SOM)
Radial Basis Function Network-Functional Link Network (FLN)
Hopfield Network
Unit III: Fuzzy Logic
9
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 Genetic
Unit IV: Genetic Algorithms
6
Introduction
Encoding –Fitness Function-Reproduction operators
Genetic Modeling –Genetic operators
Cross over
Mutation
Generational cycle-convergence of Genetic Algorithm
Unit V: Applications of AI Techniques
8
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
Multi-layer perceptron using Back propagation Algorithm (BPA)
Description
Practice Questions
Additional Notes
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