AKTU Application of Soft Computing (RCS071) Question Paper 2020-21

Note: Attempt all Sections. If require any missing data; then choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 7 = 14 marks

1. Write the applications of Neuro Fuzzy System.
2. What are the properties of fuzzy sets?
3. Write the applications of Artificial Neural Networks.
4. Draw a flowchart of implementation steps of genetic algorithm (GA).
5. Outline the differences between hard computing and soft computing.
6. What is fuzzification?
7. Write the applications of genetic algorithm.

Section B

Q2. Attempt any three of the following · 7 × 3 = 21 marks

1. Explain in detail the architecture of Mc Culloch – Pitts neuron model and also realize 3-input NAND gate, NOR gate using the above neuron model.
2. Explain about the training algorithms for pattern association.
3. Explain about the cardinalities in fuzzy sets.
4. Explain air conditioner control using fuzzy logic.
5. Define the terms chromosome, fitness function, crossover and mutation as used in genetic algorithms.

Section C

Q3

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain about the classification taxonomy of artificial neural networks.
2. Explain about the Perceptron training algorithms

Q4

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain the architectural details and algorithm of “ADALINE” model.
2. Explain about back propagation learning.

Q5

Attempt any one part of the following · 7 × 1 = 7 marks

1. What is meant by membership function? Explain in detail various membership functions of fuzzy logic systems.
2. Explain decision making using fuzzy composition operations.

Q6

Attempt any one part of the following · 7 × 1 = 7 marks

1. What are the basic components of a fuzzy logic system? Explain each of them in detail.
2. Explain applications of fuzzy logic in control system with one example.

Q7

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain in detail about various operators of genetic algorithm and also explain genetic algorithm evaluation procedure.
2. A genetic algorithm is to be used to evolve a binary string of length n containing only 1s. The initial population is a randomly generated set of binary strings of length n. Give a suitable fitness function for this problem.

Short on time? See the most repeated AKTU Application of Soft Computing questions across all years.

Other years

More AKTU Soft Computing papers on LearnAIFast.

This paper is reproduced for study purposes only. Copyright belongs to AKTU. Source: the question paper bank of ABES Institute of Technology, an AKTU-affiliated college. If you own the copyright and want it removed, email learnwithskillnest@gmail.com and we will take it down.