The Department of Electrical and Electronics Engineering, School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore conducted a IETE Sponsored two days Workshop on Soft Computing Techniques during March 11-12, 2017.
This workshop covers Fuzzy Logic and Artificial Neural Networks, Genetic Algorithm and Simulated Annealing. Soft Computing refers to the science of reasoning, thinking and deduction that recognizes and uses the real-world phenomena of grouping, memberships, and classification of various quantities under study. As such, it is an extension of natural heuristics and capable of dealing with complex systems because it does not require strict mathematical definitions and distinctions for the system components. It differs from hard computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The main techniques in soft computing are artificial neural networks, simulated annealing, genetic algorithm and particle swarm optimization. Each technique can be used separately, but a powerful advantage of soft computing is the complementary nature of the techniques. Used together they can produce solutions to problems that are too complex or inherently noisy to tackle with conventional mathematical methods. The applications of soft computing have proved two main advantages. First, it made solving nonlinear problems, in which mathematical models are not available, possible. Second, it introduced human knowledge such as cognition, recognition, understanding, learning, and others into the fields of computing. This resulted in the possibility of constructing intelligent systems such as autonomous self-tuning systems, and automated designed systems.
The platform for the transfer of knowledge in the area of soft computing technique
Speakers / Guests
Number of Participants: 60