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MMTE-007 Soft Computing and Its Applications (4 Credits)
“Soft Computing and its Applications” is a 4-credit course. This course involves theory component as well as practical component. In this course the three main components of soft computing, fuzzy logic, neural networks and genetic algorithms are discussed with applications. The prerequisite dependency for this course is “Probability and Statistics”, (MMT-008) which you would have studied during the second semester of the programme. This course comprises four blocks related to soft computing. It begins with fuzzy set, and fuzzy C-mean algorithm in Block 1. The next two blocks discuss neural network with its applications. In the last block, the course concludes with several genetic algorithms. The practical assignments are listed at the end of corresponding unit.
Block 1 Fuzzy Sets
Unit 1 Fuzzy Set - An Introduction
Unit-1.pdfUnit 2 Fuzzy Clustering
Unit-2.pdfUnit 3 Fuzzy Pattern Recognition
Unit-3.pdfBlock 2 Neural Networks I
Unit 4 Fundamentals of Neural Networks
Unit-4.pdfUnit 5 Single Layer Perceptrons
Unit-5.pdfUnit 6 Multi Layer Perceptrons
Unit-6.pdfBlock 3 Neural Networks II
Unit 7 Applications of MLP
Unit-7.pdfUnit 8 Radial Basis Function Networks
Unit-8.pdfUnit 9 Hopfield Networks
Unit-9.pdfUnit 10 Kohonen Networks
Unit-10.pdfBlock 4 Genetic Algorithm (GA)
Unit 11 Simple Genetic Algorithm
Unit-11.pdfUnit 12 Applications of Genetic Algorithm
Unit-12.pdfUnit 13 The Schema Theorem
Unit-13.pdfReport abuse