Anna University OEC552 Soft Computing 2017 Regulation Notes, Question Banks, Two Marks with Answers, Previous Year Question Papers and Syllabus.
OEC552 SOFT COMPUTING
UNIT I INTRODUCTION TO SOFT COMPUTING:
Soft Computing Constituents-From Conventional AI to Computational Intelligence- Artificial neural network: Introduction, characteristics- learning methods – taxonomy – Evolution of neural networks - basic models - important technologies - applications. Fuzzy logic: Introduction - crisp sets- fuzzy sets - crisp relations and fuzzy relations: cartesian product of relation - classical relation, fuzzy relations, tolerance and equivalence relations, non-iterative fuzzy sets. Genetic algorithm- Introduction - biological background - traditional optimization and search techniques - Genetic basic concepts.
UNIT II NEURAL NETWORKS:
McCulloch-Pitts neuron - linear separability - hebb network - supervised learning network: perceptron networks - adaptive linear neuron, multiple adaptive linear neuron, BPN, RBF, TDNN- associative memory network: auto-associative memory network, hetero-associative memory network, BAM, hopfield networks, iterative auto associative memory network and iterative associative memory network –unsupervised learning networks: Kohonen self-organizing feature maps, LVQ – CP networks, ART network.
UNIT III FUZZY LOGIC:
Membership functions: features, fuzzification, methods of membership value assignments- Defuzzification: lambda cuts - methods - fuzzy arithmetic and fuzzy measures: fuzzy arithmetic - extension principle - fuzzy measures - measures of fuzziness -fuzzy integrals - fuzzy rule base and approximate reasoning : truth values and tables, fuzzy propositions, formation of rules- decomposition of rules, aggregation of fuzzy rules, fuzzy reasoning-fuzzy inference systems- overview of fuzzy expert system-fuzzy decision making.
UNIT IV GENETIC ALGORITHM:
Genetic algorithm- Introduction - biological background - traditional optimization and search techniques - Genetic basic concepts - operators – Encoding scheme – Fitness evaluation – crossover - mutation - genetic programming – multilevel optimization – real life problem- advances in GA.
UNIT V HYBRID SOFT COMPUTING TECHNIQUES and APPLICATIONS:
Neuro-fuzzy hybrid systems - genetic neuro hybrid systems - genetic fuzzy hybrid and fuzzy genetic hybrid systems - simplified fuzzy ARTMAP - Applications: A fusion approach of multispectral images with SAR, optimization of traveling salesman problem using genetic algorithm approach, soft computing based hybrid fuzzy controllers.
2017 Regulation
PPT Notes:
OEC552 Soft Computing PPT Notes - Click here
Question Bank:
OEC552 Soft Computing QBank - Click here
Two Marks:
OEC552 Soft Computing 2Marks - Click here
Previous Year Question Paper:
NovDec 2017 - Click here
AprilMay 2017 - Click here
NovDec 2016 - Click here
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