Fuzzy Logic MCQs in Math

By: Prof. Dr. Fazal Rehman Shamil | Last updated: November 25, 2024

Q1: In fuzzy logic, what does a membership function represent?

  • (A) A function that maps each input to a fuzzy set
  • (B) A function that maps each input to a crisp value
  • (C) A function that maps fuzzy sets to outputs
  • (D) A function that computes the degree of truth of an input

Answer: (A) A function that maps each input to a fuzzy set

Q2: In fuzzy logic, which of the following is NOT a commonly used t-norm (triangular norm)?

  • (A) Minimum T-norm
  • (B) Product T-norm
  • (C) Maximum T-norm
  • (D) Lukasiewicz T-norm

Answer: (C) Maximum T-norm

Q3: What is the output of a fuzzy inference system?

  • (A) A crisp output from a fuzzy set
  • (B) A fuzzy output
  • (C) A set of rules
  • (D) A continuous function

Answer: (B) A fuzzy output

Q4: Which of the following is a key feature of fuzzy logic compared to classical Boolean logic?

  • (A) Fuzzy logic allows partial membership values between 0 and 1
  • (B) Fuzzy logic uses only true and false values
  • (C) Fuzzy logic does not use set theory
  • (D) Fuzzy logic operates only with continuous variables

Answer: (A) Fuzzy logic allows partial membership values between 0 and 1

Q5: Which method is commonly used in fuzzy logic to perform the aggregation of multiple fuzzy sets?

  • (A) Minimum aggregation
  • (B) Maximum aggregation
  • (C) Arithmetic mean aggregation
  • (D) Weighted average aggregation

Answer: (D) Weighted average aggregation

Q6: What is the primary advantage of using fuzzy logic in control systems?

  • (A) It allows for precise control based on exact measurements
  • (B) It simplifies complex control systems into binary decisions
  • (C) It allows for handling of imprecision and uncertainty in decision-making
  • (D) It eliminates the need for human intervention in control systems

Answer: (C) It allows for handling of imprecision and uncertainty in decision-making

Q7: In fuzzy logic, what does defuzzification refer to?

  • (A) Converting a fuzzy output to a crisp value
  • (B) Mapping input values to fuzzy sets
  • (C) Combining multiple fuzzy sets into one
  • (D) Defining membership functions for fuzzy sets

Answer: (A) Converting a fuzzy output to a crisp value

Q8: What is the purpose of fuzzy rules in a fuzzy inference system?

  • (A) To provide crisp inputs for fuzzy sets
  • (B) To convert crisp outputs to fuzzy outputs
  • (C) To map fuzzy inputs to fuzzy outputs based on certain conditions
  • (D) To optimize the membership function of fuzzy sets

Answer: (C) To map fuzzy inputs to fuzzy outputs based on certain conditions