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Syllabus Soft Computing - (410253(B)) CreditExamination Scheme : 03In-Sem (Paper) : 30 Marks End-Sem (Paper) : 70 Marks Unit IIntroduction To Soft Computing Introduction to Soft Computing and Computational Intelligence, Characteristics of Soft computing, Comparison Soft Computing Vs Hard Computing, Requirements of Soft Computing, Soft Computing Techniques - Artificial Neural Network, Fuzzy Logic., Evolutionary computing and Hybrid systems, Applications of Soft Computing. (Chapter - 1) Unit II Artificial Neural Network Neuron, Nerve structure and synapse, Artificial Neuron and its model, activation, functions, Neural network architecture: single layer and multilayer feed forward networks, recurrent networks. Various learning techniques; perception and convergence rule, Auto-associative and hetro - associative memory, perceptron model, single layer artificial neural network, multilayer perceptron model; back propagation learning methods, effect of learning rule coefficient; back propagation algorithm, factors affecting backpropagation training, applications. (Chapter - 2) Unit III Evolutionary Computing Problem Solving as A Search Task, Hill Climbing And Simulated Annealing, Evolutionary Computing, Evolution Strategies, Evolutionary Programming, Genetic Programming, Selected Applications From The Literature: A Brief Description, Scope Of Evolutionary Computing, Introduction to Evolutionary Single-Objective Optimization, Particle Swarm Optimization : Introduction, inspiration, mathematical model, standard and binary PSO. Artificial hummingbird algorithm. (Chapter - 3) Unit IV Fuzzy Logic Introduction to Fuzzy Logic, Classical Set, Fuzzy Set - Introduction, Operations on classical sets, properties of classical sets, fuzzy set operations, properties of fuzzy sets, Classical Relation, Fuzzy Relation, Fuzzy Inference process - Membership functions, Fuzzification, Membership value Assignment - Inference, Rank ordering, defuzzification - Weighted Average Method, Mean-Max Membership, Fuzzy Bayesian Decision Making, Developing a Fuzzy Control - System Architecture and Operation of FLC System, FLC System Models, Application of FLC System. (Chapter - 4) Unit V Genetic Algorithm Introduction To Basic Terminologies in Genetic Algorithm : Individuals, Genes, Fitness, Populations; Simple GA; General Genetic Algorithm; Operators in Genetic Algorithm : Encoding, Selection, Crossover (Recombination), Mutation; Stopping Condition for GA Flow; Constraints in Genetic Algorithms; Problem Solving Using Genetic Algorithm; Holland Classifier System : The Production System, The Bucket Brigade Algorithm and Rule Generation; Advantages and Limitations of Genetic Algorithms; Applications of Genetic Algorithms. (Chapter - 5) Unit VI Hybrid System and Application Areas of Soft Computing Hybrid System towards comprehensive Soft Computing : The hybrid systems paradigm, Hybrid connectionist production systems, Hybrid connectionist logic programming systems, Hybrid fuzzy connectionist production systems, Hybrid systems for speech and language processing, Hybrid systems for decision making. Application Areas of Soft Computing : Fuzzy-filtered Neural Networks-Plasma Spectrum Analysis, Hand-written Numeral Recognition, Fuzzy sets and Genetic Algorithms in Game Playing, Soft Computing for Color Recipe Prediction. (Chapter - 6)