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,
The course is of interdisciplinary nature and students from
ME, etc. can take this course.
UG/PG :Both UG and PG
INDUSTRY SUPPORT :
All IT companies, in general.
3662 students have enrolled already!!
Debasis Samanta holds a Ph.D. in
Computer Science and Engineering from Indian Institute of Technology Kharagpur.
His research interests and work experience spans the areas of Computational
Intelligence, Data Analytics, Human Computer Interaction, Brain Computing and
Biometric Systems. Dr. Samanta currently works as a faculty member at the
Department of Computer Science & Engineering at IIT Kharagpur.
COURSE LAYOUT :
Week 1: Introduction to Soft Computing, Introduction to Fuzzy logic,Fuzzy membership functions,Operations on Fuzzy sets
Week 4: Solving optimization problems, Concept of GA, GA Operators: Encoding,GA Operators: Selection-I
Week 5: GA Operators: Selection-II, GA Operators: Crossover-I, GA Operators: Crossover-II, GA Operators: Mutation
Week 6:Introduction to EC-I, Introduction to EC-II, MOEA Approaches: Non-Pareto, MOEA Approaches: Pareto-I
Week 7: MOEA Approaches: Pareto-II, Introduction to ANN, ANN Architecture
Week 8: ANN Training-I, ANN Training-II, ANN Training-III, Applications of ANN
Introduction to Genetic Algorithm Melanic Mitchell (MIT Press)
Algorithm for Solving Multi-objective, Optimization Problems (2nd
Edition), Collelo, Lament, Veldhnizer ( Springer) 3. Fuzzy
Logic with Engineering Applications Timothy J. Ross (Wiley) 4. Neural
Networks and Learning Machines Simon Haykin (PHI)
The exam is optional for a fee.
Date and Time of Exams: April 28 (Saturday) and April 29 (Sunday) : Morning session 9am to 12noon.
Exam for this course will be available in one session on both 28 and 29 April.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published.
Final score will be calculated as : 25% assignment score + 75% final exam score
25% assignment score is calculated as 25% of average of 08 weeks course: Best 06 out of 08 assignments
E-Certificate will be given to those who register and write the exam and score greater than or equal to 40%
final score. Certificate will have your name, photograph and the score in the final exam with the breakup. It
will have the logos of NPTEL and IIT Kharagpur. It will be e-verifiable at nptel.ac.in/noc.