QB ECC604 May 2022 Examination TE EXTC Sem VI 2021-22.xlsx

	A	B	C	D
1		Q=QUESTION	question_description	question_type
2		A=ANSWER	answer_description	answer_isright
3	Sr. No.
4	1	Q	Sigmoidal functions are:	M
5		A	Hard limiting activation functions	0
6		A	Soft limiting activation functions	1
7		A	Hard-Soft limiting activation functions	0
8		A	Soft-Hard limiting activation functions	0
9	2	Q	In relationship between biological and artificial neurons: Cell represents	M
10		A	interconnection	0
11		A	Weight	0
12		A	Output	0
13		A	Neuron	1
14	3	Q	In relationship between biological and artificial neurons: Axon represents	M
15		A	Neuron	0
16		A	Output	1
17		A	weight	0
18		A	Interconnection	0
19	4	Q	Weights in MP Neuron model can take values:	M
20		A	0 and 1	0
21		A	1 and -1	1
22		A	1 and 0	0
23		A	-1 and -1	0
24	5	Q	Symptoms of overfitting are:	M
25		A	Low bias, High variance	1
26		A	Low bias, Low variance	0
27		A	High bias, Low variance	0
28		A	High bias, High variance	0
29	6	Q	Symptoms of underfitting are:	M
30		A	High bias, High variance	1
31		A	Low bias, Low variance	0
32		A	Low bias, High variance	0
33		A	High bias, Low variance	0
34	7	Q	Epoch represents:	M
35		A	Iteration	1
36		A	Presenting one input to ANN	0
37		A	Presenting some inputs to ANN	0
38		A	Presenting all inputs to ANN multiple times	0
39	8	Q	___________ can be used to process non-linear dataset.	M
40		A	Perceptron – Multilayer	1
41		A	Perceptron - Single Layer	0
42		A	MP Neuron	0
43		A	Artificial Neuron	0
44	9	Q	Mexican Hat Net is a:	M
45		A	negative net competitive network	0
46		A	Fix net competitive network	1
47		A	variable net competitive network	0
48		A	positive net competitive network	0
49	10	Q	In hopfield model, when a unit is selected at random and its new state is computed, it is	M
50		A	synchronous update	0
51		A	asynchronous update	1
52		A	synchronously asynchronous update	0
53		A	asynchronously synchronous update	0
54	11	Q	In Hopfield model, when all units are updated simultaneously, it is	M
55		A	synchronous update	1
56		A	asynchronous update	0
57		A	synchronously asynchronous update	0
58		A	asynchronously synchronous update	0
59	12	Q	K means is _______ algorithm.	M
60		A	Classification	0
61		A	association rule	0
62		A	clustering	1
63		A	neural network	0
64	13	Q	K means algorithm is ____________	M
65		A	unsupervised	1
66		A	supervised	0
67		A	reinforcement and supervised	0
68		A	reinforcement	0
69	14	Q	What will not be a descriptor if distance is input variable?	M
70		A	Distance	1
71		A	Long Distance	0
72		A	Short Distance	0
73		A	Medium Distance	0
74	15	Q	Which is the last step, when applying fuzzy controller to any system?	M
75		A	fuzzification	0
76		A	database creation	0
77		A	defuzzification	1
78		A	rule base creation	0
79	16	Q	In home heating system, if the temperature is cool. Then cool descriptor of temperature represents use of linguistic variable is used can be represented by _______	M
80		A	Crisp Set	0
81		A	Fuzzy Set	1
82		A	Binary Set	0
83		A	Real value set	0
84	17	Q	A and B are fuzzy sets then, following expression shows Commutative property	M
85		A	A∪B = B∪A	1
86		A	A∪B = B∩A	0
87		A	A∩B = A∪B	0
88		A	A∩B = B∪A	0
89	18	Q	Algebraic product of fuzzy sets A and B is equal to:	M
90		A	Min(1, μA(x)* μB(x))	0
91		A	μA(x)* μB(x)	1
92		A	Max(1, μA(x)* μB(x))	0
93		A	Min(0, μA(x)* μB(x))	0
94	19	Q	Bounded sum of fuzzy sets A and B is equal to:	M
95		A	μA(x)+ μB(x)	0
96		A	Max(1, μA(x)+μB(x))	0
97		A	Min(1, μA(x)+ μB(x))	1
98		A	Min(0, μA(x)+ μB(x))	0
99	20	Q	Crosspoint of a fuzzy set has membership value:	M
100		A	between 0 and 1	0