13MCA554 Soft Computing syllabus for MCA


Unit-1 Genetic Algorithm: An Overview 5 hours

History of Evolutionary Computing, The Appeal of Evolution, Biological Terminology, Elementsof Genetic Algorithm, Genetic Algorithms and Traditional Search Methods, Applications andExamples of Genetic Algorithm.

Unit-2 Genetic Algorithm in Problem Solving 5 hours

Evolving Computer Programs, Data Analysis and Prediction, Evolving Neural Networks.

Unit-3 Theoretical Foundations of Genetic Algorithm 5 hours

Schemas and the Two-Armed Bandit Problem, Royal Roads, Exact Mathematical Models ofGenetic Algorithm

Unit-4 Implementing a Genetic Algorithm 5 hours

When should a Genetic Algorithm be used , Encoding a Problem for a Genetic Algorithm,Adapting the Encoding, Selection Methods , Genetic Operators, Parameters for GeneticAlgorithm.

Unit-5 Introduction to fuzzy set theory 8 hours

Probabilistic reasoning, Fuzzy sets, Mathematics of fuzzy set theory, Operations on fuzzy sets,Comparison of fuzzy and crisp set theory.

Unit-6 Fuzzy mapping 6 hours

One to one mapping, Max-min principle, Extension principle, Implication rules – mamdaniimplications.

Unit-7 Membership functions 8 hours

Universe of discourse, Mapping inside fuzzy domain, Fuzzy membership mapping methods,Application to real world problems.

Unit-8 Neural Networks and Fuzzy System 6 hours

Neural and Fuzzy Machine Intelligence, Fuzziness as Multivalence, The Dynamical SystemApproach to Machine Intelligence: The Brain as a Dynamical System, Intelligent Behaviour asAdaptive Model Free estimation.

Unit-9 Neural Network Theory 4 hours

Neuron as Functions, Signal Monotonicity, Biological Activations and Signals, Neuron Fields,Neuronal Dynamical System, Common Signal Functions, Pulse –Coded Signal Functions

Last Updated: Tuesday, January 24, 2023