McqMate
These multiple-choice questions (MCQs) are designed to enhance your knowledge and understanding in the following areas: Uncategorized topics .
| 301. |
What are the applications of Fuzzy Inference Systems? |
| A. | Wireless services, heat control and printers |
| B. | Restrict power usage, telephone lines and sort data |
| C. | Simulink, boiler and CD recording |
| D. | Automatic control, decision analysis and data classification |
| Answer» D. Automatic control, decision analysis and data classification | |
| 302. |
Which of the following is not true regarding the principles of fuzzy logic ? |
| A. | Fuzzy logic follows the principle of Aristotle and |
| B. | Japan is currently the most active users of fuzzy logic |
| C. | Fuzzy logic is a concept of 'certain degree' |
| D. | Boolean logic is a subset of fuzzy logic |
| Answer» A. Fuzzy logic follows the principle of Aristotle and | |
| 303. |
Suppose, a fuzzy set Young is defined as follows Young = (10, 0.5), (20, 0.8), (30, 0.8), (40, 0.5), (50, 0.3) Then the crisp value of Young using MoM method is |
| A. | 20 |
| B. | 25 |
| C. | 30 |
| D. | 35 |
| Answer» B. 25 | |
| 304. |
What Is Fuzzy Inference Systems? |
| A. | The process of formulating the mapping from a given input to an output using fuzzy |
| B. | The process of formulating the mapping from a given input to an output using fuzzy |
| C. | Having a larger output than the input |
| D. | Having a smaller output than the input |
| Answer» A. The process of formulating the mapping from a given input to an output using fuzzy | |
| 305. |
Mamdani's Fuzzy Inference Method Was Designed To Attempt What? |
| A. | Control any two combinations of any two products by synthesising a set of linguistic control rules obtained from experienced human operations. |
| B. | Control a television and remote combination by synthesising a set of linguistic control rules obtained from experienced human operations. |
| C. | Control a steam engine and a boiler combination by synthesising a set of linguistic control rules obtained from experienced human operations |
| D. | Control a air craft and feul level combination by synthesising a set of linguistic control rules obtained from experienced human operations |
| Answer» C. Control a steam engine and a boiler combination by synthesising a set of linguistic control rules obtained from experienced human operations | |
| 306. |
R=(AXB)U(ÃXY) is |
| A. | Zadeh's Max Product rule for If x is A then y is B else y is C |
| B. | Zadeh's Max Min rule for If x is A then y is B |
| C. | Zadeh's Max Product rule for If x is A then y is B else y is C |
| D. | Zadeh's Max Min rule for If x is A then y is B |
| Answer» D. Zadeh's Max Min rule for If x is A then y is B | |
| 307. |
Sequence of steps in EA |
| A. | initialization-> selection- >mutation- >crossover- >termination |
| B. | initialization-> selection- >crossover- >termination |
| C. | initialization-> selection->crossover- >mutation- >termination |
| D. | None of these |
| Answer» C. initialization-> selection->crossover- >mutation- >termination | |
| 308. |
How many genes will be in the alphabet of the algorithm? |
| A. | n*(n-1)/2 |
| B. | n*(n+1)/2 |
| C. | n*(n-2)/2 |
| D. | n*(n+2)/2 |
| Answer» A. n*(n-1)/2 | |
| 309. |
Which of the following is not true for Genetic algorithms? |
| A. | It is a probabilistic search algorithm |
| B. | It is guaranteed to give global optimum solutions |
| C. | If an optimization problem has more than one solution, then it will return all the solutions |
| D. | It is an iterative process suitable for parallel programming |
| Answer» B. It is guaranteed to give global optimum solutions | |
| 310. |
Which one of the following is not necessarily be considered as GA parameters? |
| A. | the population size. |
| B. | the obtainable accuracy |
| C. | the mutation probability |
| D. | the average fitness score |
| Answer» D. the average fitness score | |
| 311. |
Which of the following optimization problem(s) can be better solved with Order GA? |
| A. | 0-1 Knapsack problem |
| B. | Travelling salesman problem |
| C. | Job shop scheduling problem |
| D. | Optimal binary search tree construction problem |
| Answer» B. Travelling salesman problem | |
| 312. |
If crossover between chromosomes in search space does not produce significantly different offspring, what does it imply? (if offspring consist of one half of each parent)
|
| A. | ii, iii & iv only |
| B. | ii, iii only |
| C. | i, iii & iv only |
| D. | All of the mentioned |
| Answer» B. ii, iii only | |
| 313. |
In Rank‐based selection scheme, which of the following is not correct |
| A. | The % area to be occupied by an individual , is given by average of sumation of elements |
| B. | Two or more individuals with the same fitness values should have the same rank. |
| C. | Individuals are arranged in a descending order of their fitness values. |
| D. | The proportionate based selection scheme is followed based on the assigned rank. |
| Answer» C. Individuals are arranged in a descending order of their fitness values. | |
| 314. |
Real Coded GA flow is- |
| A. | Random mutation- Polynomial mutation |
| B. | Polynomial mutation-Random mutation |
| C. | Flipping-Random mutation- Polynomial mutation |
| D. | None |
| Answer» A. Random mutation- Polynomial mutation | |
| 315. |
Breeding in GA flow is- |
| A. | Create a mating pool- Select a pair- Reproduce |
| B. | Select a pair-Create a mating pool- Reproduce |
| C. | Reproduce-Create a mating pool- Select a pair |
| D. | None |
| Answer» A. Create a mating pool- Select a pair- Reproduce | |
| 316. |
Binary Coded GA flow is- |
| A. | Flipping- Interchanging- Reversing |
| B. | Reversing- Flipping- Interchanging- |
| C. | Interchanging- Reversing-Flipping |
| D. | None |
| Answer» A. Flipping- Interchanging- Reversing | |
| 317. |
Which of the following comparison is true? |
| A. | In the event of restricted accessto information, GAs win out in that they require much |
| B. | Under any circumstances, GAs always outperform other algorithms. |
| C. | The qualities of solutions offered by GAs for any problems are always better than |
| D. | GAs could be applied to any problem, whereas certain algorithms are applicable to |
| Answer» A. In the event of restricted accessto information, GAs win out in that they require much | |
| 318. |
Premature convergence of PSO is |
| A. | Once PSO traps in global optimum, it is dificult to jump out of global optimum |
| B. | Once PSO traps in local optimum, it is dificult to jump out of local optimum |
| C. | Once PSO traps in local optimum, it is dificult to jump out of global optimum |
| D. | Once PSO traps in global optimum, it is dificult to jump out of local optimum |
| Answer» B. Once PSO traps in local optimum, it is dificult to jump out of local optimum | |
| 319. |
Takugi-Sugeno approach to FLC design is computationally more expensive compared to Mamdani approach because |
| A. | Mamdani approach considers a less number of rules in fuzzy rule base |
| B. | Searching a rule in Mamdani approach is simple and hence less time consuming |
| C. | Takagi-Sugeno approach consider a large number of rules in fuzzy rule base |
| D. | Computation of each rule in Takagi-Sugeno approach is more time consuming |
| Answer» D. Computation of each rule in Takagi-Sugeno approach is more time consuming | |
| 320. |
When we say that the boundary is crisp |
| A. | Distinguish two regio |
| B. | Cannot Distinguis |
| C. | Collection of ordere |
| D. | None of these |
| Answer» A. Distinguish two regio | |
| 321. |
Core of soft computing is |
| A. | Fuzzy computing,neu |
| B. | Fuzzy network an |
| C. | Neural Science |
| D. | Genetic Science |
| Answer» A. Fuzzy computing,neu | |
| 322. |
Fuzzy Computing |
| A. | mimics human behav |
| B. | deals with inpreci |
| C. | exact information |
| D. | both a and b |
| Answer» D. both a and b | |
| 323. |
Hard computing is also called as |
| A. | evolutionary comput |
| B. | conventional com |
| C. | non conventional co |
| D. | probablistic computing |
| Answer» B. conventional com | |
| 324. |
Neural network computing |
| A. | mimics human behav |
| B. | information proce |
| C. | both a and b |
| D. | none of the above |
| Answer» C. both a and b | |
| 325. |
How does blind search differ from optimization |
| A. | Blind search represe |
| B. | Blind search usua |
| C. | Blind search cannot |
| D. | none of these |
| Answer» B. Blind search usua | |
| 326. |
In modeling,an optimal solution is understood to be |
| A. | a solution that can o |
| B. | a solution found i |
| C. | a solution that is th |
| D. | a solution that require |
| Answer» C. a solution that is th | |
| 327. |
When is a complete enumeration of solution used? |
| A. | When a solution that |
| B. | When there is en |
| C. | When the modeler |
| D. | When there are an infi |
| Answer» B. When there is en | |
| 328. |
All of the follwing are true about heuristics EXCEPT |
| A. | heuristics are used w |
| B. | heuristics are use |
| C. | heuristics are used |
| D. | heuristics are rules of |
| Answer» C. heuristics are used | |
| 329. |
Genetic algorithm belong to the family of method in the |
| A. | artifical intelligence a |
| B. | optimization area |
| C. | complete enumerat |
| D. | Non computer based i |
| Answer» A. artifical intelligence a | |
| 330. |
What does the 0 membership value means in the set |
| A. | the object is fully insi |
| B. | the object is not i |
| C. | the object is partiall |
| D. | none of the above |
| Answer» B. the object is not i | |
| 331. |
The union of two fuzzy sets is the of each element from two sets |
| A. | maximum |
| B. | minimum |
| C. | equal to |
| D. | not equal to |
| Answer» A. maximum | |
| 332. |
The process of fuzzy interference system involes |
| A. | membership function |
| B. | fuzzy logic operat |
| C. | if-then rules |
| D. | all the above |
| Answer» D. all the above | |
| 333. |
What does a fuzzifier do |
| A. | coverts crisp input to |
| B. | coverts crisp oupu |
| C. | coverts fuzzy input |
| D. | coverts fuzzy output to |
| Answer» A. coverts crisp input to | |
| 334. |
Which of the folloowing is not defuzzifier method |
| A. | centroid of area |
| B. | mean of maximu |
| C. | largest of maximum |
| D. | hypotenuse of triangle |
| Answer» D. hypotenuse of triangle | |
| 335. |
A Fuzzy rule can have |
| A. | multiple part of ante |
| B. | only single part of |
| C. | multiple part of ant |
| D. | only single part of ante |
| Answer» C. multiple part of ant | |
| 336. |
The intersection of two fuzzy sets is the of each element from two sets |
| A. | maximum |
| B. | minimum |
| C. | equal to |
| D. | not equal to |
| Answer» B. minimum | |
| 337. |
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the co |
| A. | m{0/a,0.7/b,0.8/c,0.2/ |
| B. | {0/a,0.9/b,0.7/c,0 |
| C. | {0.8/a,0.7/b,0.8/c,0 |
| D. | {0/a,0.7/b,0.8/c,0.9/d, |
| Answer» A. m{0/a,0.7/b,0.8/c,0.2/ | |
| 338. |
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the uni |
| A. | {1/a,0.9/b,0.1/c,0.5/ |
| B. | {0.8/a,0.9/b,0.2/c |
| C. | {1/a,0.9/b,0.2/c,0.8 |
| D. | {1/a,0.9/b,0.2/c,0.8/d, |
| Answer» C. {1/a,0.9/b,0.2/c,0.8 | |
| 339. |
A={1/a,0.3/b,0.2/c,0.8/d,0/e} B={0.6/a,0.9/b,0.1/c,0.3/d,0.2/e} What will be the inte |
| A. | {0.6/a,0.3/b,0.1/c,0.3 |
| B. | {0.6/a,0.8/b,0.1/c |
| C. | {0.6/a,0.3/b,0.1/c,0 |
| D. | {0.6/a,0.3/b,0.2/c,0.3/ |
| Answer» A. {0.6/a,0.3/b,0.1/c,0.3 | |
| 340. |
Fuzzy logic deals with which of the following |
| A. | fuzzy set |
| B. | fuzzy algebra |
| C. | both a and b |
| D. | none of the above |
| Answer» C. both a and b | |
| 341. |
which of the following is a sequence of steps taken in designning a fuzy logic machine |
| A. | fuzzification->Rule Ev |
| B. | deffuzification->r |
| C. | rule evaluation->fuz |
| D. | rule evaluation->defuz |
| Answer» A. fuzzification->Rule Ev | |
| 342. |
All of the follwing are suitable problem for genetic algorithm EXCEPT |
| A. | pattern recognization |
| B. | simulation of biol |
| C. | simple optimization |
| D. | dynamic process contr |
| Answer» C. simple optimization | |
| 343. |
Tabu search is an example of ? |
| A. | heuristic |
| B. | Evolutionary algo |
| C. | ACO |
| D. | PSO |
| Answer» A. heuristic | |
| 344. |
Genetic algorithms are example of |
| A. | heuristic |
| B. | Evolutionary algo |
| C. | ACO |
| D. | PSO |
| Answer» B. Evolutionary algo | |
| 345. |
mutation is applied on candidates. |
| A. | one |
| B. | two |
| C. | more than two |
| D. | noneof these |
| Answer» A. one | |
| 346. |
recombination is applied on candidates. |
| A. | one |
| B. | two |
| C. | more than two |
| D. | noneof these |
| Answer» B. two | |
| 347. |
LCS belongs to based methods? |
| A. | rule based learning |
| B. | genetic learning |
| C. | both a and b |
| D. | noneof these |
| Answer» A. rule based learning | |
| 348. |
Survival is approach. |
| A. | deteministic |
| B. | non deterministic |
| C. | semi deterministic |
| D. | noneof these |
| Answer» A. deteministic | |
| 349. |
Evolutionary algorithms are a based approach |
| A. | heuristic |
| B. | metaheuristic |
| C. | both a and b |
| D. | noneof these |
| Answer» A. heuristic | |
| 350. |
Chromosomes are actually ? |
| A. | line representation |
| B. | String representa |
| C. | Circular representat |
| D. | all of these |
| Answer» B. String representa | |
Done Studing? Take A Test.
Great job completing your study session! Now it's time to put your knowledge to the test. Challenge yourself, see how much you've learned, and identify areas for improvement. Don’t worry, this is all part of the journey to mastery. Ready for the next step? Take a quiz to solidify what you've just studied.