Aktu Application of Soft Computing (KCS-056) Btech Syllabus

Explore the Application of Soft Computing in the AKTU B.Tech syllabus, including how fuzzy logic, neural networks, and evolutionary algorithms are used to solve challenging real-world situations. Utilise the power of advanced computational methods.

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UNIT-1: NEURAL NETWORKS-I

• Neuron, Nerve structure and synapse, A
• rtificial 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.

UNIT-2: NEURAL NETWORKS-II

• Architecture: perceptron model, solution,
• Single layer artificial neural network,
• Multilayer perception model;
• Back propagation learning methods,
• Effect of learning rule co-efficient;
• Back propagation algorithm,
• Factors affecting back propagation training, applications.

UNIT-3: FUZZY LOGIC-I

• Basic concepts of fuzzy logic,
• Fuzzy sets and Crisp sets,
• Fuzzy set theory and operations,
• Properties of fuzzy sets,
• Fuzzy and Crisp relations,
• Fuzzy to Crisp conversion.

UNIT-4: FUZZY LOGIC-II

• Membership functions,
• Interference in fuzzy logic,
• Fuzzy if-then rules,
• Fuzzy implications and Fuzzy algorithms,
• Fuzzyfications & Defuzzificataions,
• Fuzzy Controller,
• Industrial applications.

UNIT-5: GENETIC ALGORITHM

• Basic concepts,
• Working principle,
• Procedures of GA,
• Flow chart of GA,
• Genetic representations, (encoding) Initialization and selection,
• Genetic operators, Mutation,
• Generational Cycle, applications.

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