BE Computer Engineering Semester 7 (BE Fourth Year)University of Mumbai

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Soft Computing Semester 7 (BE Fourth Year) BE Computer Engineering University of Mumbai Topics and Syllabus

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CBCGS [2019 - current]
CBGS [2015 - 2018]
Old [2000 - 2014]

Topics with syllabus and resources

100.00 Introduction to Soft Computing
  • Soft computing Constituents, Characteristics of Neuro Computing and Soft Computing, Difference between Hard Computing and Soft Computing, Concepts of Learning and Adaptation.
200.00 Neural Networks
201.00 Basics of Neural Networks
  • Introduction to Neural Networks, Biological Neural Networks, McCulloch Pitt model.
202.00 Supervised Learning Algorithms
  • Perceptron (Single Layer, Multi layer), Linear separability, Delta learning rule, Back Propagation algorithm.
203.00 Un-supervised Learning Algorithms
  • Hebbian Learning, Winner take all, Self Organizing Maps, Learning Vector Quantization.
300.00 Fuzzy Set Theory
  • Classical Sets and Fuzzy Sets, Classical Relations and Fuzzy Relations, Properties of membership function, Fuzzy extension principle, Fuzzy Systems- fuzzification, defuzzification and fuzzy controllers.
400.00 Hybrid System
  • Introduction to Hybrid Systems, Adaptive Neuro Fuzzy Inference System (ANFIS).
500.00 Introduction to Optimization Techniques
  • Derivative based optimization- Steepest Descent, Newton method.
  • Derivative free optimization- Introduction to Evolutionary Concepts.
600.00 Genetic Algorithms and Its Applications
  • Inheritance Operators, Cross over types, inversion and Deletion, Mutation Operator, Bit-wise Operators, Convergence of GA, Applications of GA.
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