Q1)
1) State any two strengths of GA.
2) Explain the linguistic hedge - Intensification.
3) State the equation of Gaussian membership function.
4) Define fuzzy set.
5) State any two basic operations in GA.
6) What is supervised learning?
7) State the components of a neural network.
8) What is mutation?
9) Define selection
10) Define Fuzzy sets
11) What is membership function?
12) State
any two basic operators in genetic algo.
13)
Define convex fuzzy set.
14)
State any 2 applications of GA.
15)
What is perceptron learning Rule.
16)
State the components of a neural network.
Q2)
1) What is defuzzification? Explain the weighted average
and mean-max
2) What is membership methods for Defuzzifying fuzzy
output.
3) Explain the features of membership function.
4) Explain disadvantages and advantages of GA.
5) Explain binary neuron structure in detail.
6) Explain any 2 properties of neural network.
7) Explain what is unsupervised learning.
8) Define linear separability and show that the 2D Boolean
function XOR is linearly non-separable
9) What is the main difference between single
layer and multilayer Artificial Neural network?
Draw the Structure of typical biological neurons
10)
Consider
two given Fuzzy sets
11) A= {½+ 0.3/4+ 0.5/6+ 0.2/8}B= {0.5/2+ 0.4/4+ 0.1/6+ 1/8}
Perform union and complement over fuzzy set A&B
14)
Explain
any 2 properties of neural network.
15)
Explain
what is unsupervised learning.
16)
What
are the salient properties of Neural Network?
17)
Explain
any two genetic operators on schema.
18)
Define
union operations of fuzzy sets with an appropriate example.
19)
Give
advantages of Genetic Algorithm
20)
Write
any four applications of Neural Network
21)
Explain
fuzzy set operations.
22)
What
are the features of membership functions.
23)
What
is difference between supervised learning and unsupervised learning.
24)
What
are the types of Architectures of Neural Network?
25)
How
Genetic Algorithms are different from traditional methods.
26)
Explain
MSE error surface and its geometry.
27)
What
are the applications of Fuzzy logic.
28)
What
is defuzzification? Explain the centroid and weighted average methods.
29)
Explain
concept of convex fuzzy sets. What is fuzzy number.
30)
Explain
any four properties of GA.
31)
Briefly
outline the procedure of gradient descent-based learning.
32)What is alpha-cut method?
Milan Tomic
Hi. I’m Designer of Blog Magic. I’m CEO/Founder of ThemeXpose. I’m Creative Art Director, Web Designer, UI/UX Designer, Interaction Designer, Industrial Designer, Web Developer, Business Enthusiast, StartUp Enthusiast, Speaker, Writer and Photographer. Inspired to make things looks better.
0 comments:
Post a Comment