## NPTEL Introduction To Soft Computing Week 3 Assignment Answers 2024

1. Which fuzzy inference system approach prioritizes interpretability at the expense of accuracy?

a. Mamdani approach

b. Takagi and Sugeno’s approach

c. Both approaches provide the same level of interpretability and accuracy.

d. The choice depends on the specific application and its priorities.

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2. What does the term “linguistic hedges” refer to in a fuzzy logic system?

a. Techniques for defining the universe of discourse

b. Methods for calculating membership values

c. Modifiers that adjust the meaning of linguistic terms

d. Algorithms for fuzzy inference

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3. Consider a fuzzy logic system where the input variable is “Temperature” ranging from 0°C to 50°C. The fuzzy sets for this variable are defined as “Cold”, “Warm”, and “Hot”. The membership function for the “Warm” set is a triangular function defined by the points (10,0),(25,1),(40,0), where the function increases linearly from 10°C to 25°C and decreases linearly from 25°C to 40°C. If the current temperature is 30°C, what is the membership value of the “Warm” set?

a. 0.33

b. 0.5

c. 0.75

d. 0.67

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4. Consider a fuzzy logic system that controls a heater in a room. The system takes two inputs: the temperature x and the humidity y. The fuzzy sets for x are Cold and Hot with membership functions μCold(x) and μHot(x), respectively. Similarly, the fuzzy sets for y are Dry and Wet with membership functions μDry(y) and μWet(y), respectively. The output z controls the heater and has Low and High fuzzy sets.

The system has two rules:

1. If the room is Cold and Dry, then the heater is set to Low.

2. If the room is Hot and Wet, then the heater is set to High.

Now, suppose on a particular day, the membership functions for the inputs are as follows: μCold(x) = 0.4, μHot(x) = 0.6, μDry(y) = 0.5, and μWet(y) = 0.5. Can you compute the rule strengths for the two rules?

a. 0.5, 0.5

b. 0.2, 0.3

c. 0.4, 0.5

d. 0.24,0.25

Answer :-

5. High interpretability is followed by the fuzzy logic controller (s)

a. Mamdani approach

b. Takagi and sugeno’s approach

c. Both a, b

d. None of the above

Answer :-

6. Limitations of the traditional optimization approaches are

a. Discrete (integer) variables are difficult to handle.

b. Method may not be suitable for parallel computing.

c. Methods may not necessarily be adaptive.

d. All the above.

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7. The genetic algorithm works based on the mechanisms of

a. Neural network and natural language processing

b. Natural genetics and natural evaluation.

c. Artificial intelligence and machine learning.

d. None of these.

Answer :-

8. Combinatorial optimization is

a. NP‐Hard problem

b. NP‐complete problem

c. Scholastic Assessment problem

d. None of the above

Answer :-

9. In Steady-state Genetic algorithm

a. Population size is small and Chromosomes are of longer length.

b. Population size is small and Chromosomes are of smaller length.

c. Population size is large and Chromosomes are of smaller length.

d. Population size is large and Chromosomes are of longer length.

Answer :-

10. Fuzzy Logic Controller contains

a. Fuzzy rule base

b. Fuzzy inference engine

c. A fuzzification module

d. All the above

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