

McqMate
These multiple-choice questions (MCQs) are designed to enhance your knowledge and understanding in the following areas: Uncategorized topics .
101. |
What Is Another Name For Fuzzy Inference Systems? |
A. | fuzzy expert system |
B. | fuzzy modelling |
C. | fuzzy logic controller |
D. | all of the above |
Answer» D. all of the above |
102. |
In Evolutionary programming, survival selection is |
A. | probabilistic selection (μ+μ) selection |
B. | (μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children |
C. | children replace the parent |
D. | all the mentioned |
Answer» A. probabilistic selection (μ+μ) selection |
103. |
In Evolutionary strategy, survival selection is |
A. | probabilistic selection (μ+μ) selection |
B. | (μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children |
C. | children replace the parent |
D. | all the mentioned |
Answer» B. (μ, λ)- selection based on the children only (μ+λ)- selection based on both the set of parent and children |
104. |
In Evolutionary programming, recombination is |
A. | doesnot use recombination to produce offspring. it only uses mutation |
B. | uses recombination such as cross over to produce offspring |
C. | uses various recombination operators |
D. | none of the mentioned |
Answer» A. doesnot use recombination to produce offspring. it only uses mutation |
105. |
In Evolutionary strategy, recombination is |
A. | doesnot use recombination to produce offspring. it only uses mutation |
B. | uses recombination such as cross over to produce offspring |
C. | uses various recombination operators |
D. | none of the mentioned |
Answer» B. uses recombination such as cross over to produce offspring |
106. |
Step size in non-adaptive EP : |
A. | deviation in step sizes remain static |
B. | deviation in step sizes change over time using some deterministic function |
C. | deviation in step size change dynamically |
D. | size=1 |
Answer» A. deviation in step sizes remain static |
107. |
Step size in dynamic EP : |
A. | deviation in step sizes remain static |
B. | deviation in step sizes change over time using some deterministic function |
C. | deviation in step size change dynamically |
D. | size=1 |
Answer» B. deviation in step sizes change over time using some deterministic function |
108. |
Step size in self-adaptive EP : |
A. | deviation in step sizes remain static |
B. | deviation in step sizes change over time using some deterministic function |
C. | deviation in step size change dynamically |
D. | size=1 |
Answer» C. deviation in step size change dynamically |
109. |
What are normally the two best measurement units for an evolutionary algorithm?
|
A. | 1 and 2 |
B. | 2 and 3 |
C. | 3 and 4 |
D. | 1 and 4 |
Answer» D. 1 and 4 |
110. |
Evolutionary Strategies (ES) |
A. | (µ,λ): select survivors among parents and offspring |
B. | (µ+λ): select survivors among parents and offspring |
C. | (µ-λ): select survivors among offspring only |
D. | (µ:λ): select survivors among offspring only |
Answer» B. (µ+λ): select survivors among parents and offspring |
111. |
In Evolutionary programming, |
A. | individuals are represented by real-valued vector |
B. | individual solution is represented as a finite state machine |
C. | individuals are represented as binary string |
D. | none of the mentioned |
Answer» B. individual solution is represented as a finite state machine |
112. |
In Evolutionary Strategy, |
A. | individuals are represented by real-valued vector |
B. | individual solution is represented as a finite state machine |
C. | individuals are represented as binary string |
D. | none of the mentioned |
Answer» A. individuals are represented by real-valued vector |
113. |
(1+1) ES |
A. | offspring becomes parent if offspring\s fitness is as good as parent of next generation |
B. | offspring become parent by default |
C. | offspring never becomes parent |
D. | none of the mentioned |
Answer» A. offspring becomes parent if offspring\s fitness is as good as parent of next generation |
114. |
(1+λ) ES |
A. | λ mutants can be generated from one parent |
B. | one mutant is generated |
C. | 2λ mutants can be generated |
D. | no mutants are generated |
Answer» A. λ mutants can be generated from one parent |
115. |
Termination condition for EA |
A. | mazimally allowed cpu time is elapsed |
B. | total number of fitness evaluations reaches a given limit |
C. | population diveristy drops under a given threshold |
D. | all the mentioned |
Answer» D. all the mentioned |
116. |
Which of the following operator is simplest selection operator? |
A. | random selection |
B. | proportional selection |
C. | tournament selection |
D. | none |
Answer» A. random selection |
117. |
Which crossover operators are used in evolutionary programming? |
A. | single point crossover |
B. | two point crossover |
C. | uniform crossover |
D. | evolutionary programming doesnot use crossover operators |
Answer» D. evolutionary programming doesnot use crossover operators |
118. |
(1+1) ES |
A. | operates on population size of two |
B. | operates on populantion size of one |
C. | operates on populantion size of zero |
D. | operates on populantion size of λ |
Answer» A. operates on population size of two |
119. |
Which of these emphasize of development of behavioral models? |
A. | evolutionary programming |
B. | genetic programming |
C. | genetic algorithm |
D. | all the mentioned |
Answer» A. evolutionary programming |
120. |
EP applies which evolutionary operators? |
A. | variation through application of mutation operators |
B. | selection |
C. | both a and b |
D. | none of the mentioned |
Answer» C. both a and b |
121. |
Which selection strategy works with negative fitness value? |
A. | roulette wheel selection |
B. | stochastic universal sampling |
C. | tournament selection |
D. | rank selection |
Answer» D. rank selection |
122. |
Who can deal with noisy input information |
A. | soft computing |
B. | hard computing |
C. | both a and b |
D. | none of the above |
Answer» A. soft computing |
123. |
Ability to learn how to do task based on the data is done by |
A. | self organization |
B. | adaptive learning |
C. | fault tolerance |
D. | robustness |
Answer» B. adaptive learning |
124. |
Which of the following is not a technique of soft computing |
A. | neural network |
B. | genetic algorithm |
C. | evolutionary algorithm |
D. | conventional algorithm |
Answer» D. conventional algorithm |
125. |
Fuzzy logic system is based on what type of rule |
A. | if-then |
B. | else-if |
C. | while |
D. | do-while |
Answer» A. if-then |
126. |
What is the function of dendrites in biological neural network |
A. | send signals to neurons |
B. | receive signals from neurons |
C. | sum of incoming signals |
D. | transmit signals |
Answer» B. receive signals from neurons |
127. |
Expert system |
A. | combines different types of method and information |
B. | is a approach to design of learning algorithms |
C. | is an information base filled with knowledge of an expert formulated in terms of if-then rules |
D. | none of the above |
Answer» C. is an information base filled with knowledge of an expert formulated in terms of if-then rules |
128. |
Three main basic feature involved in characterzing member function are |
A. | intuition,inference,rank ordering |
B. | fuzzy algorithm,neural network,genetic algorithm |
C. | center of sums,median,core |
D. | core,support,boundary |
Answer» D. core,support,boundary |
129. |
What is the function of cell body in biological neural network |
A. | multiplies the incoming signals |
B. | sums the incoming signals |
C. | multiples the outgoing signals |
D. | sums the outgoing signals |
Answer» B. sums the incoming signals |
130. |
What is perceptron |
A. | a single layer feed forward neural network |
B. | a double layer associative neural network |
C. | a neural network that contains feedback |
D. | auto associative neural network |
Answer» A. a single layer feed forward neural network |
131. |
Which of the follwing computing is trial and error problem solver algorithm |
A. | hard computing |
B. | neural network |
C. | evolutionary computing |
D. | fuzzy logic |
Answer» C. evolutionary computing |
132. |
What are advantages of neural network |
A. | ability to learn by example |
B. | fault tolerant |
C. | both a and b |
D. | none of the above |
Answer» C. both a and b |
133. |
Which of the following does not belong to the process of involuntary computing |
A. | selection |
B. | mutation |
C. | recombination |
D. | deletion |
Answer» D. deletion |
134. |
The Value of crisp set can be |
A. | either 0 or 1 |
B. | near to 0 or 1 |
C. | between 0 and 1 |
D. | between 0.5 and 0.7 |
Answer» A. either 0 or 1 |
135. |
The room temrature is hot. Here the hot(use of lingustic variable is used) can be represented by |
A. | fuzzy set |
B. | crisp set |
C. | probabilistic set |
D. | none of the above |
Answer» A. fuzzy set |
136. |
The value of set membership can be represented by |
A. | discrete set |
B. | degree of truth |
C. | probabilities |
D. | both b and c |
Answer» B. degree of truth |
137. |
Semiconductor layout & aircraft design are the application type of which domain? |
A. | control |
B. | design |
C. | robotics |
D. | ml |
Answer» B. design |
138. |
Trajectory planning is the application type of which domain? |
A. | control |
B. | design |
C. | robotics |
D. | ml |
Answer» C. robotics |
139. |
Filter design is the application type of which domain? |
A. | control |
B. | signal processing |
C. | robotics |
D. | ml |
Answer» B. signal processing |
140. |
Pokers & Checkers are the application type of which of domain? |
A. | control |
B. | game playing |
C. | robotics |
D. | ml |
Answer» B. game playing |
141. |
Manufacturing & resource allocation are the application type of which domain? |
A. | scheduling |
B. | design |
C. | robotics |
D. | ml |
Answer» A. scheduling |
142. |
What is a crossover point in a fuzzy set? |
A. | {x|ua(x)<0} |
B. | {x|ua(x)=1} |
C. | {x|ua(x)=0.5} |
D. | {x|ua(x)>0} |
Answer» C. {x|ua(x)=0.5} |
143. |
If A and B are two fuzzy sets with membership function: Ua(X)={0.2,0.5,0.6,0.1,0.9} Ub(X0)={0.1,0.5,0.2,0.7,0.8} THEN what will be the intersection of A and B |
A. | {0.2,0.5,0.6,0.7,0.9} |
B. | {0.2,0.3,0.8,0.1,0.5} |
C. | {0.5,0.1,0.6,0.1,0.8} |
D. | {0.1,0.5,0.2,0.1,0.8} |
Answer» D. {0.1,0.5,0.2,0.1,0.8} |
144. |
A={0.1/1+0.2/2+0.3/3} B={0.6/1+0.5/2+0.4/3+0.5/4} Find the set difference |
A. | {0.1/1+0.2/2+0.3/3} |
B. | {0.3/1+0.2/2+0.2/3} |
C. | {0.1/1+0.3/2+0.2/3} |
D. | {0.1/1+0.2/2+0.5/3} |
Answer» A. {0.1/1+0.2/2+0.3/3} |
145. |
With the help of which formula can we find the algebraic sum of two fuzzy sets A,B? |
A. | {ua(x)+ub(x)}-{ua(x)*ub(x)} |
B. | {ua(x)-ub(x)}-{ua(x)*ub(x)} |
C. | {ua(x)/ub(x)}-{ua(x)+ub(x)} |
D. | {ua(x)+ub(x)}+{ua(x)*ub(x)} |
Answer» A. {ua(x)+ub(x)}-{ua(x)*ub(x)} |
146. |
With the help of which formula can we find the algebraic product of two fuzzy sets A,B? |
A. | {ua(x)/ub(x)} |
B. | {ua(x)*ub(x)}*{ua(x)-ub(x)} |
C. | {ua(x)*ub(x)+{ua(x)+ub(x)}} |
D. | {ua(x)*ub(x)} |
Answer» D. {ua(x)*ub(x)} |
147. |
Which one of the following is the associative property for a crisp set |
A. | au(buc)=(aub)uc |
B. | bu(auc)=cu(bua) |
C. | au(cua)=b(auc) |
D. | all the above |
Answer» A. au(buc)=(aub)uc |
148. |
Knowledge base is a combination of |
A. | rule base and data base |
B. | rule base and time base |
C. | time base and probability base |
D. | model base and data base |
Answer» A. rule base and data base |
149. |
_____ is a simulation method that let decision maker see what the model is doing and how it interact. |
A. | vis |
B. | vim |
C. | siv |
D. | hiv |
Answer» A. vis |
150. |
____systems,especially those developed for the military and video-game industry |
A. | vis |
B. | vim |
C. | siv |
D. | hiv |
Answer» B. vim |
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