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M.Sc. (Information Technology) SEM I 2023 2024 Feb 2024 SOFT COMPUTING TECHNIQUES Question Paper - Mumbai University | munotes

M.SC. (INFORMATION TECHOLOGY) SEM I FEB.24 SOFT COMPUTING TECHNIQUES (PD 14 FEB.24) (PC 58021).pdf
SEM I · 2023 - 2024 · 1 May 2025

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Newer exam Feb 2024 - RESEARCH METHODOLOGY Semester-end · 2023 2024 →

Questions asked in this paper

  1. Q1 Attempt any two of the following: 10 marks
    • a. Distinguish between hard computing and soft computing
    • b. What is bi-directional associative memory? List the activation functions used in
    • c. Write a short note on Fuzzy Logic
    • d. State the advantages and limitation of genetic algorithm
  2. Q2 Attempt any two of the following: 10 marks
    • a. Define Soft Computing. State various type of soft computing techniques and explain any two types in details
    • b. Obtain the output of the neuron Y for the network shown in figure given below using activation functions as: (i) binary sigmoidal and (ii) bipolar sigmoidal
    • c. With suitable diagram explain the concept of linear separability with OR function
    • d. the training phase of the Back-propagation algorithm
  3. Q3 Attempt any two of the following: 10 marks
    • a. What is spiking neural networks? Explain Izhikevich Neuron Model
    • b. Discuss the important features of Kohonen self-organizing maps
    • c. a short note on Optical Neural Network
    • d. Mexican Hat? Draw and explain its structure in detail
  4. Q4 Attempt any two of the following: 10 marks
    • a. Define convex and non-convex fuzzy set. Explain the angular fuzzy set method of fuzzification in details
    • b. What is fuzzy measure? State and explain the axioms of fuzzy measures & and
    • c. What is fuzzy composition? Consider the two fuzzy relation R and S given below
    • d. Lambda cut in fuzzy set? Explain strong and weak Lambda cut in detail with
  5. Q5 Attempt any two of the following: 10 marks
    • a. What is fuzzy logic controller? State and explain the components of FLC
    • b. | Write a short note on neuro-fuzzy hybrid systems
    • c. With suitable example, explain one-point and two-point crossover techniques in
    • d. in details the four modes of approximate reasoning

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