Tiêu đề wSoft Computing Tech. 2022(odd) Suppl.pdf ✅

42CI252C699ACID7D76560AB4NFEZ3549 Page l of 5 2020505A (d) none of these (raã á à nt ad) (c) (b) individual solution is represented as a finite state (3) In (d) None of these (ran e àt at) in terrns of if-then rules. (c) Decision support systerns that contain an Information base (b) Approach to the design of learning algorithms that is structured along the lines of the theory of evolution. (2) Combining different types of method or information (faf wER Á fafiy aiY 1 t) Evolutionary computation is (fasmart (d) to be sure you've read the question (ufafsre à ers fr và vg fear t) (c) be to (b) to be sure you've got the right cause (u efAfaa à fers f (a) to be sure you know the answer. (e fafare àfy f at 4KI fuer rar ) iii. The absolute first step of problem solving is ard 3 ) (d) None of these (reà TÔ) (c) (b) Initial state (tf HAar) (a) The Set of actions for a problem in a state space is formulated by a... (w) (a) (stfam fevfa) state Last (b) Intermediate state (c) (d) all of these A problem in a scarch space is defined by one of these state. Q.1 Choose the most suitable answer the following options. (1*20-20) Group (A) (u ) Marks are mentioned on the right side of' each question. (at# nft w Æ sitt sfaa fa ) All questions are conipulsory. (nt v afurd t) Hours] (Time: 3 Soft Computing Techniques (2020505A) Engineering) (Eleetrical (Theory) Marks: |Full. 70] SEM-V IDiploma Exam 2022 (Odd) Supp/Comp. Roll No: individuals are represented as binary string (fn ) e fign à e à cutu i) machine (afd uNa à vkfaa de qenn à y À qfun uu t) individuals are represented by rea]-valued vector (afn à eafa- HH àN T tar atdt ) Evolutionary progranming(fuEaA ufm H,) filled with the knowledge of an expert formulated uroar t) sure you are you (efafsa fy fa HN S7T) Successor function. which takes current action and returns next immediate state. Intermediate states (adi 4aAI) Initial state sbte.way2poly.in
42C1252C699ACD7D76560AB48PE73549 Page 2 of 5 202050S.A (affe) (a) fcalure mppin (b) (e m) apping patten (c) atn) (e4 (d) one of these xív. For what purpose Feedbuck ncural networks ure primarily used? (a) subnormal fuzzy sets (b) nornal fuzzy set (c) convex fuzzy sel (3e ee) (4det de) (d) concave fuzzy set xiii A fuzzy set wherein no membersiip funclion bas its value equal to I is called. (e (a) subnormal fuzzy sets nz) (b) normal fuzzy set (c) convex fuzzy set (set 2) (d) concave fuzzy set value is unity is called A fuzzy set whose membership function has at least one element x in the universe whose membership evaluation Rule(d) Fuzzification HetEA (fa4u evaluation Rule(c) ’Fuzzification ’ Defuzzification tsfafkzfafrz) What are the following sequence of steps taken in designing a fuzzy logie machine? (b) gaps are not inserted (3terer (a) scquence is changed ( W sIe à ) T) (d) gaps are not In Genetic Algorithm, in the mutation process..... (3Rtada) (a) b) Function Fitness (c) (rfers a) Selection Naural(d) Which of the following operation is responsible to jump from one hill to another hill? (b) evolutionary algorithm (frent qerttea) heuristic (sq) (a) (d) Particle swarm optimization (* A) (c) Ant colony optimization (ft t E) vi. Genetic algorithms are example of (b) (a) win win spiral model (faa f wiget se) (d) all of these (rai à nt) (c) vii. Which one of the tenination (ra) (a) selection (b) recombination (tia) (c) initialization (iu)(d) vi. What is the first step in Evolutionary algorithn? classification Defuzzification (fr4 eq04A ’ffuàz -- tafaftàz) (b) Fuzzification Defuzzification -’ Rule evaluation ’wfafvàHfAq4 (sfafANA Hetea) (a) Fuzzification ’ Rule evaluation --’ Defuzzification (sffàzH’ fruH ete’frfka) rearranged (3Brer 4akafeA TË RAT ) (c) scquence is not changed (qH A0 Vet re ) Mutation Cross over ineremental model (aazter tee) concurent development model (uaf fau trse) following is not an Evolutionary Process Mdl? (*) sbte.way2poly.in
42C252C69ACDD6560AB4XIF73549 Page of53 202050S (d) Once PSO traps in global optimum, it is diflicult to jump out of local optinum (c) Once PSO traps in local optimum, it is difficult to jump out of global optimum (b) Once PSO traps in local optimum, it is difficult to jump out of local optimum (a) Once PSO traps in global optimum, it is difficult to jump out of global optimum (PSO qusá sfuvn t) Premature convergence of PSO is (aíse x) optimum global (a) optimum local (b) (atu AH) sf) (afy maximum global (c) minimum local (d) Where does PSO 1,2 (2) 1,2,3 (b) 2,3,4 (c) (raÁ fe~u yfae ? 1) rquw it uaitt 2) fta ieit- eittt 3) fhuusn 4) vfvt gTefi enteu:) (d) all of these (s À n) algorithms: Swarm Kvi. (d) none of these (ra t a) (c) (b) Basis function (AR URr ferr) (a) Ivii. Pattern recall takes more tinme for (d) none of these ( à) (c) on the basis of average gradient value (a4a aIeT H 3TK U) (b) no heuristic criteria exist (t 4Prt HR0E t Tt ) (a) there is convergence involved (sñ sshr fre t) wi. How can the leaming process be stopped in backpropagation rule? (d) all of these (s à à n) (c) there is no feedback of signal at any stage (fft 4 fae âgt at tar t) (b) emor in output is propagated backward only to determine weight updates (a) it is also Which of the following is true regarding the backpropagation rule? clustering based terninates? intelligence includes: l) bee colony algorithm 2) ant colony algorithn1 3) PSO 4) immune system Equal for both MLFNN and basis function (aUVUAUA 0t 3rg e t fers HHTa) feedforward Multilayer neural networks (aedt ftg ia get Aza à feru) called the generalized delta rule (sà ana fu v-t 61 H ) sbte.way2poly.in
Group (B) (qu -) 0.2 Classify different search algorithms. Deseribe anyonc. Explain the Breadth-first search method of the scarch algorithm. 03 Compare Evolutionary programming and Genetie Programming. OR (3rU) 04 Explain Ant colony optimization technique. Describe various operators of the Genetic Algorithm. Compare soft computing vs. hard computing. OR (ra) OR (3at) 0.5 Explain the activation functions used in Artificial Neural Networks. OR (Ta) Compare feed forward and feedback neural networks. Q.6 Explain single-layer and multilayer feed-forward neural networks. OR (3rar) How soft computing techniques can be applied to Inventory control? Explain. Describe the A0 search algorithm in detail. (A0* ud vaitan faueu à aha ) Group (C) (gu -) Explain the terms problem, problem space, and search in the context of soft comnputing. OR (Hu) Explain the genctic Alyorithm with a low chart. Explain in brief history of Evolutionary conpuation. OR (G4) Page 4 of 5 42C1252Ch99ACD7D76560AB48FF73549 4 4 4 4 4 4 4 2020505A sbte.way2poly.in