Description
ISBN | 978-93-91334-34-5 |
Publishers | R. Narain & Co. |
Author | Nobel Editorial Board |
Binding | Paperback |
Pages | 160 |
Subject | Soft Computing |
Original price was: ₹120.₹90Current price is: ₹90.
This book is designed to meet the needs of master of computer application students studying for the very first time in their curriculum. Thus complexity of the matter has been avoided with a view that complete course content has to be completed by the student in limited time period. The subject matter has been presented in a lucid, comprehensive and systematic manner which is easy to understand and also develops writing ability for students to score good marks in upcoming examination. This book includes all types of questions according to new pattern of university. Course content has been divided into topic wise and in chapter wise form according to curriculum framed by Dr. A.P.J. Abdul Kalam Technical University, Lucknow. This book includes unsolved papers of last years and sample paper. We hope that this book will be successful in its objectives and will receive appreciation from students and teachers alike.
ISBN | 978-93-91334-34-5 |
Publishers | R. Narain & Co. |
Author | Nobel Editorial Board |
Binding | Paperback |
Pages | 160 |
Subject | Soft Computing |
Weight | 200 g |
---|---|
Dimensions | 20 × 12 × 1 cm |
Soft Computing
(KCA- 032)
Unit I – Introduction to Soft Computing: Introduction, Comparison with hardcomputing, Concept of learning and adaptation, Constituents of soft computing, Applications of soft computing.Artificial Neural Networks: Basic concepts of neural networks, Human brain, Biological neural network, History of artificial neural networks, Basic building blocks of an artificial neuron, Neural network architectures, Activation functions, Characteristics and limitation of neural networks.
Unit II – Artificial Neural Networks: Learning methods – Supervised, Unsupervised,Reinforcement, Hebbian, Gradient descent, Competitive, Stochastic.Major classes of neural networks: Perceptron networks, Multilayer perceptron model, Back-propagation network, Radial basis function network, Recurrent neural network, Hopfield networks, Kohonen self-organizing feature maps.
Unit III – Fuzzy Logic: Introduction to Fuzzy Logic, Comparison with crisp logic,Properties of classical sets, Operations on classical sets, Properties of fuzzy sets, Operations on fuzzy sets, Classical relations, Fuzzy relations, Features and types of fuzzy membership functions, Fuzzy arithmetic, Fuzzy measures.Fuzzy Systems: Crisp logic, Predicate logic, Fuzzy logic, Fuzzy propositions, Inference rules, Fuzzy inference systems- Fuzzification, Inference, Defuzzification, Types of inference engines.
Unit IV – Evolutionary Computing: Introduction, Evolutionary algorithm, Biologicalevolutionary process, Paradigms of evolutionary computing – Genetic algorithm and Genetic programming, Evolutionary strategies, Evolutionary programming.Genetic Algorithm: Introduction, Traditional optimization and search techniques, Comparison with traditional algorithms, Operations- Encoding, Selection, Crossover and Mutation, Classification of Genetic algorithm.
Unit V – Hybrid Soft Computing Techniques: Introduction, Classification of hybridsystems, Neuro-fuzzy hybrid systems, Neuro-genetic hybrid systems, Fuzzy- genetic hybrid systems.Other Soft Computing Techniques: Tabu Search, Ant colony based optimization, Swarm Intelligence.
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