Artificial Intelligence MCQs with Answers
Practice important Artificial Intelligence MCQs with answers and explanations.
Chapter: 31
Q941:
The input variables in a fuzzy inference system are first subjected to ______.
A. Optimization
B. Fuzzification
C. Defuzzification
D. Linear transformation
Correct Answer:
B
Chapter: 31
Q942:
What is the last step in the fuzzy inference process?
A. Fuzzification
B. Rule evaluation
C. Aggregation
D. Defuzzification
Correct Answer:
D
Chapter: 31
Q943:
The fuzzy operator is applied during which stage of FIS?
A. Defuzzification
B. Fuzzification
C. Antecedent evaluation
D. Output mapping
Correct Answer:
C
Chapter: 31
Q944:
The implication stage in fuzzy logic does what?
A. Assigns input membership values
B. Determines rule strength
C. Transforms inputs to crisp outputs
D. Maps antecedent truth to consequent
Correct Answer:
B
Chapter: 31
Q945:
How many key steps are there in the fuzzy inference process?
A. Three
B. Five
C. Four
D. Six
Correct Answer:
B
Chapter: 31
Q946:
The aggregation step in FIS combines outputs from ______.
A. Input functions
B. Different rules
C. Only max-value rules
D. The defuzzification unit
Correct Answer:
B
Chapter: 31
Q947:
Fuzzification is the process of ______.
A. Converting fuzzy values to crisp ones
B. Creating random values
C. Converting crisp inputs to degrees of membership
D. Executing fuzzy rules
Correct Answer:
C
Chapter: 31
Q948:
Defuzzification is necessary to obtain ______.
A. A visual representation of logic
B. A crisp output from fuzzy sets
C. Multiple fuzzy outputs
D. The rule with highest value
Correct Answer:
B
Chapter: 31
Q949:
Which fuzzy inference method is based on linguistic control rules?
A. Sugeno
B. Mamdani
C. Neuro-fuzzy
D. Fuzzy k-means
Correct Answer:
B
Chapter: 31
Q950:
Fuzzy inference systems are multidisciplinary because they apply to ______.
A. Only machine learning
B. Only mathematics
C. Various fields like control, vision, and decision making
D. Only linguistic modeling
Correct Answer:
C
Chapter: 31
Q951:
In a fuzzy tip-calculating system, the input variables are ______.
A. Service and price
B. Waiter and food
C. Service and food
D. Ambience and bill
Correct Answer:
C
Chapter: 31
Q952:
In the fuzzy dinner case study, the tip percentage varies between ______.
A. 0% to 50%
B. 10% to 30%
C. 5% to 25%
D. 1% to 10%
Correct Answer:
C
Chapter: 31
Q953:
The fuzzy rules in the dinner example help determine ______.
A. Service quality
B. Ambience rating
C. Tip percentage
D. Food quality
Correct Answer:
C
Chapter: 31
Q954:
Fuzzy expert systems are a type of ______.
A. Hardware system
B. Mechanical network
C. Fuzzy inference system
D. Relational database
Correct Answer:
C
Chapter: 31
Q955:
The output of the fuzzy inference system is ______.
A. A decision rule
B. A fuzzy value
C. A crisp number after defuzzification
D. A graph
Correct Answer:
C
Chapter: 31
Q956:
Mamdani’s method uses rules derived from ______.
A. Historical data
B. Mathematical proofs
C. Human experience
D. Simulated learning
Correct Answer:
C
Chapter: 31
Q957:
One benefit of FIS is its ability to work with ______.
A. Only binary logic
B. Only random data
C. Uncertainty and approximate reasoning
D. Only large data
Correct Answer:
C
Chapter: 31
Q958:
Defuzzification translates the fuzzy output into a ______.
A. Fuzzy conclusion
B. Multiple output set
C. Crisp actionable value
D. Linguistic term
Correct Answer:
C
Chapter: 32
Q959:
What is the first step in the fuzzy inference process?
A. Fuzzify inputs
B. Defuzzify outputs
C. Apply fuzzy operator
D. Aggregate all outputs
Correct Answer:
A
Chapter: 32
Q960:
What is the final step in the fuzzy inference system?
A. Fuzzify inputs
B. Apply implication method
C. Defuzzify
D. Apply fuzzy operator
Correct Answer:
C