Assignment 1 sc
Pacific School of Engineering
Dept: CSE Semester: 7th
Subject: Soft Computing
Assignment-1
Q. 1. Explain the working of Artificial Neuron and compare it with biological neuron
Q. 2. Discuss Back Propagation Algorithm in detail with proper illustration.
Q. 3. Compare:
I. Supervised Vs. Unsupervised Learning
II. Hard Computing Vs. Soft Computing
III. Single Layer Vs. Multilayer Perceptron
Q. 4. Write a short note on:
I. Radial Basis Function
II. LVQ
Q. 5. Discuss various operations of fuzzy sets with example.
Q. 6. Consider the two fuzzy sets A and B and given α=2:
A ={ 0.33/6 + 0.67/7 +1/8 + 0.67/9+0.33/10}
B= {0.2/6 + 0.6 /7 +1/8 + 0.8 /9 + 0.52/10}
Find (i) AUB (ii) Aα (iii) A-B
Q.7 Describe Mamdani FIS with its advantages. Differentiate between Mamdani FIS and Sugeno FIS.
Q.8 Let X={a,b,c,d} Y={1,2,3,4}Let A & B are fuzzy sets such as A={(a,0)(b,0.8)(c,0.6)(d,1)} B={(1,0.2)(2,1)(3,0.8)(4,0)}.
Determine the implication relations IF x is A THEN y is B.
Q.9 The results of three implication processes are shown in the Fig. 1.
Find the aggregated output and the defuzzyfied output using the following methods:
Center of Gravity or Centroid method
Weighted average method
Means-max method
Find out any one research paper on application of Genetic Algorithm. You can submit soft copy or hard copy. When you submit it, I will evaluate (you have to explain me).
Research paper should be since 2005.
OR (Q- 1 & 2 in File Pages only)
Q-10
Table 2 shows a population of strings of four numbers. Assuming that the string represents a binary encoding of a number n, and the fitness function is given by Fi = 100/n. Fill in the rest of the table using Rank selection algorithm to generate a matting pool of size 4. Write down the matting pool in table 3.
String No.
String
n
Fi
Fi / Σ Fi
No. of Copies Selected
1
10111
23
4.35
2
00111
3
01001
4
01010
Table 2
Mating Pool
Mate
Crossover point
New Population n New Fi
Table 3
11. Give the problem
Dept: CSE Semester: 7th
Subject: Soft Computing
Assignment-1
Q. 1. Explain the working of Artificial Neuron and compare it with biological neuron
Q. 2. Discuss Back Propagation Algorithm in detail with proper illustration.
Q. 3. Compare:
I. Supervised Vs. Unsupervised Learning
II. Hard Computing Vs. Soft Computing
III. Single Layer Vs. Multilayer Perceptron
Q. 4. Write a short note on:
I. Radial Basis Function
II. LVQ
Q. 5. Discuss various operations of fuzzy sets with example.
Q. 6. Consider the two fuzzy sets A and B and given α=2:
A ={ 0.33/6 + 0.67/7 +1/8 + 0.67/9+0.33/10}
B= {0.2/6 + 0.6 /7 +1/8 + 0.8 /9 + 0.52/10}
Find (i) AUB (ii) Aα (iii) A-B
Q.7 Describe Mamdani FIS with its advantages. Differentiate between Mamdani FIS and Sugeno FIS.
Q.8 Let X={a,b,c,d} Y={1,2,3,4}Let A & B are fuzzy sets such as A={(a,0)(b,0.8)(c,0.6)(d,1)} B={(1,0.2)(2,1)(3,0.8)(4,0)}.
Determine the implication relations IF x is A THEN y is B.
Q.9 The results of three implication processes are shown in the Fig. 1.
Find the aggregated output and the defuzzyfied output using the following methods:
Center of Gravity or Centroid method
Weighted average method
Means-max method
Find out any one research paper on application of Genetic Algorithm. You can submit soft copy or hard copy. When you submit it, I will evaluate (you have to explain me).
Research paper should be since 2005.
OR (Q- 1 & 2 in File Pages only)
Q-10
Table 2 shows a population of strings of four numbers. Assuming that the string represents a binary encoding of a number n, and the fitness function is given by Fi = 100/n. Fill in the rest of the table using Rank selection algorithm to generate a matting pool of size 4. Write down the matting pool in table 3.
String No.
String
n
Fi
Fi / Σ Fi
No. of Copies Selected
1
10111
23
4.35
2
00111
3
01001
4
01010
Table 2
Mating Pool
Mate
Crossover point
New Population n New Fi
Table 3
11. Give the problem