MC-533 ARTIFICIAL INTELLIGENCE & NEURAL NETWORKS
Credit Hours = 3
COURSE CONTENT
- Machine Intelligence Technologies (Neural Networks): Introduction to Neural Networks, Perception Learning Rule, Hebbian, and Widrow-Hoff Learning, Back propagation, Associative Learning, Competitive and Grossberg Networks. Adaptive Resonance Theory, Hopfield Networks.
- Fuzzy Set Theory: Fuzzy Set with Properties, Fuzzy Relations, Fuzzy Arithmetic, Fuzzy Logic, Applications and Fuzzy Control.
- Genetic Algorithm: Genetic Algorithm Operations, Standard, Rank, and Rank Space Method; Simulated Annealing: Annealing Process, Simulated Annealing Optimization; Particle Swarm Optimization: Swarm Behaviour, Particle Swarm Optimization.
- Artificial Intelligence: Semantic Nets and Description Matching, Generate and Test, MeansEnds Analysis, and Problem Reduction, Nets, Basic Search, and Optimal Search, Trees and Adversarial Search, Rules, Rule Chaining and Planning.
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