Soft computing is an emerging approach to computing which parallel the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision. Soft computing is based on some biological inspired methodologies such as genetics, evolution, ant’s behaviors, particles swarming, human nervous systems, etc. Now, soft computing is the only solution when we don’t have any mathematical modeling of problem solving (i.e., algorithm), need a solution to a complex problem in real time, easy to adapt with changed scenario and can be implemented with parallel computing. It has enormous applications in many application areas such as medical diagnosis, computer vision, hand written character recondition, pattern recognition, machine intelligence, weather forecasting, network optimization, VLSI design, etc.
INTENDED AUDIENCE :
- The course is of interdisciplinary nature and students from
- ME, etc. can take this course.
INDUSTRY SUPPORT :All IT companies, in general.
COURSE LAYOUT Week 1:
Introduction to Soft Computing, Introduction to Fuzzy logic,Fuzzy membership functions,Operations on Fuzzy setsWeek 2:
Fuzzy relations, Fuzzy propositions, Fuzzy implications,Fuzzy inferencesWeek 3:
Defuzzyfication Techniques-I, Defuzzyfication Techniques-II, Fuzzy logic controller-I,Fuzzy logic controller-II
Solving optimization problems, Concept of GA, GA Operators: Encoding,GA Operators: Selection-I
GA Operators: Selection-II, GA Operators: Crossover-I, GA Operators: Crossover-II,GA Operators: Mutation
Introduction to EC-I, Introduction to EC-II, MOEA Approaches: Non-Pareto,MOEA Approaches: Pareto-I
MOEA Approaches: Pareto-II, Introduction to ANN,ANN Architecture
ANN Training-I, ANN Training-II, ANN Training-III,Applications of ANN