Course: B.Tech (Semester V) Subject Code: KCS-056
Subject Name: Application of Soft Computing Time: 3 Hours
Total Marks: 100
Section A – Short Answer Questions (2 × 10 = 20 Marks)
Answer all questions briefly:
Meaning of convergence in neural networks Applications of associative memory
Limitations of the backpropagation algorithm Definition of the perceptron model
Use of fuzzy logic Operations of crisp sets
Applications of fuzzy controllers Definition of fuzzification
Applications of genetic algorithms Operators used in genetic algorithms
Section B – Descriptive Questions (10 × 3 = 30 Marks)
Attempt any three:
Recurrent auto-associative memory: advantages and disadvantages
Working of multilayer perceptron and problems in backpropagation
Operations used in fuzzy sets with examples
Importance of defuzzification and its types with examples
Different selection methods in genetic algorithms
Section C – Long Answer Questions (10 × 5 = 50 Marks)
Artificial Neural Networks (ANN):
Structure and layers of ANN Synapse and structure of a neuron
Neural Network Models:
Single-layer ANN and perceptron model Backpropagation algorithm with example
Fuzzy Logic:
Fuzzy relationships and difference between fuzzy and crisp logic
Basic components of a fuzzy logic system
Fuzzy Logic Applications:
Industrial uses of fuzzy logic Fuzzy implication and fuzzy controllers with real-life examples
Genetic Algorithms:
Two-point and uniform crossover Procedure of Genetic Algorithm