Artificial Intelligent application to Power System
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Follow on Instagram for UpdatesArtificial Intelligent application to Power System Syllabus — Unit-wise Content
The official GTU curriculum for Artificial Intelligent application to Power System (subject code 2720719) as prescribed for EE · Semester 2 divides the course into 4 units, covering 34 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (2720719)Unit 1 Introduction
- definition of AI difference between soft computing techniques and hard computing systems
- expert systems brief history of ANN, Fuzzy and GA
Unit 2 Artificial Neural Networks
- History of neural network research
- Basic concepts of Neural Networks
- Human brain
- Model of Artificial Neuron
- Neural Network architectures
- Single layer feed forward Network
- Multi layer feed forward network
- recurrent networks
- characteristics of NN, Learning Methods Perceptron
- ADALINE MADALINE Networks
- Architecture of Back propagation Network
- Non linear activation operators
- single and multilayer ANN, learning methods like Back propagation
- LM etc. training and testing of ANN
Unit 3 Fuzzy Logic
- Comparison between Fuzzy and crisp logic
- Fuzzy sets
- Membership function
- Basic fuzzy set operations
- properties of Fuzzy set, fuzzy relations
- Fuzzy interference system
- Fuzzy rule based system
- defuzzification methods
Unit 4 Genetic Algorithm
- Working principles
- difference between GA and traditional methods
- Different types of coding methods
- fitness function
- different types GA operators 1
- Roulette wheel selection 2
- Stochastic remainder Roulette wheel selection
- Rank selection
- Tournament selection and stochastic universal sampling
- different types of cross over methods in GA
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