(SEM IV) THEORY EXAMINATION 2021-22 INTRODUCTION TO SOFT COMPUTING

SECTION A 

Section A asks basic concepts like artificial vs biological neurons, soft computing vs traditional computing, crisp vs fuzzy sets, defuzzification, probability vs fuzzy theory, crossover, mutation, and selection methods. Each answer must be 4–6 lines, explaining the meaning and purpose of the concept.

Extra sample questions:
Explain fuzzy inference in a short paragraph.
Describe membership function in 4–5 lines.
Explain supervised learning briefly.

SECTION B 

Section B contains deeper questions such as MLP model, fuzzy set operations, fuzzy controller example, generation cycle of GA, and soft computing in search techniques. Answers should be one complete paragraph explaining the concept, its working, and its application.

Extra sample questions:
Describe backpropagation learning in paragraph form.
Explain types of fuzzy membership functions.
Explain the working of a simple genetic algorithm cycle.

SECTION C 

Section C includes long, detailed questions like Hopfield network, supervised learning, fuzzy logic uses in AI, fuzzy implication relations, defuzzification methods, selection methods, genetic operators, and TSP using GA.
Each answer should be a long paragraph explaining the full concept or process with examples.

Extra sample questions:
Explain in detail how fuzzy controllers are designed.
Describe the architecture and functioning of a Hopfield network.
Explain the complete working of a genetic algorithm with phases.