www.studentyogi.com                                                                         www.studentyogi.com

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www.studentyogi.com                                                                        www.studentyogi.com

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www.studentyogi.com                                                                         www.studentyogi.com

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www.studentyogi.com                                                                     www.studentyogi.com

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www.studentyogi.com                                                                        www.studentyogi.com

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www.studentyogi.com                                                                    www.studentyogi.com

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www.studentyogi.com                                                                                 www.studentyogi.com

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www.studentyogi.com                                                                       www.studentyogi.com

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Fuzzy Logic And Application Jntu Model Paper{Www.Studentyogi.Com}

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Fuzzy Logic And Application Jntu Model Paper{Www.Studentyogi.Com}

  1. 1. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 1 IV B.Tech II Semester Regular Examinations, Apr/May 2007 FUZZY LOGIC AND APPLICATION (Electrical & Electronic Engineering) Time: 3 hours Max Marks: 80 Answer any FIVE Questions All Questions carry equal marks 1. Explain the operations on crisp sets by using Venn diagrams? [16] 2. In a computer engineering di erent logic families are often compared on the basis of their power-delay pro duct. The fuzzy set F is the logic families F={NMOS, CMOS, TTL, ECL, JJ}. The range of delay time D= {0.1, 1, 10, 100} in Nano seconds. The power dissipation in micro watts P= {0.01, 0.1, 1, 10, 100} By using max-min composition to obtain a fuzzy relation between delay time and Power dissipation. [16] 3. Write a note on futures of the fuzzy membership function? [16] 4. These exercises use Zadeh’s extension principel (i)01234567 ~ 0.0 0.1 0.6 0.8 0.9 0.7 0.1 0.0 ~ 0.0 1.0 0.7 0.5 0.2 0.1 0.0 0.0 If x and y are real numbers de ned by sets ~ and ~ respectively. Calculate the fuzzy set ~ representing the real numbers Z given by (a) Z = 3x-2 (b) Z = 4x2+3 [16] 5. v3 is not a rational number; i.e., show that it can not be the ratio of two even integers by contradiction? [16] 6. Write a short notes on aggregation of fuzzy rules and explain about determination of aggregation strategy. [16] 7. In making a decision to purchase a air plane, air line management will consider the qualities of an air plains performance with respect to the competitor. The Boeing 737 is the best selling airplane in aviation history and continues to outsell its more modern competitor the A 320 manufactured by the air bus consortium. The four factors to be considered are range payload, operating cost, and reliability. The criteria will be comparison of 737 with respect to A320: superior (sup.) equivalent
  2. 2. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 1 (eq.) and de cient (def.) 073 181 ~= 154 721 Air lines weighting factors of the four factors as ~ = {.15, .15, .3, .4} nd the fuzzy vectors for the evaluation. [16] 8. As a company issuing bank cards. We want to separate individuals holding personal credit cards into two groups: pro table card holders usually let a nonzero balance on the card go from month to month, thereby accruing interest: and a eventually always pay the total balance. Unpro table card holders often do not pay a balance, and card privileges usually have to be cancelled. Suppose the data for the jth card holder consist of three features: Xj = (X11,X21,X31) where X11 = account balance X21 = amount paid X31 = amount purchased Suppose we want to classify four individuals, each characterized by the following normalized data: X1 = (1, .75, 1) X2 = (0, 0, -.5) X3 = (.5, .5, .75) X4 = (1, -.5, -.5) Note that the values (features) in each vector are normalized Gaussian variables such that = 0 and = 1, where Value=(X- c)/ c Hence, values at zero are at the mean of a class (c), positive values indicate a variable greater than the mean, and negative values indicate a variable less than the mean. Use the following 2-partition as the initial guess, and nd the optimum 2-partition. (0) = 1 1 0 0 [16] 0011
  3. 3. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 2 IV B.Tech II Semester Regular Examinations, Apr/May 2007 FUZZY LOGIC AND APPLICATION (Electrical & Electronic Engineering) Time: 3 hours Max Marks: 80 Answer any FIVE Questions All Questions carry equal marks 1. (a) Explain the di erence between randomness and fuzziness. (b) Describe the concept of a fuzzy set in your own words. [16] 2. In a computer engineering di erent logic families are often compared on the basis of their power-delay pro duct. The fuzzy set F is the logic families F={NMOS, CMOS, TTL, ECL, JJ}. The range of delay time D= {0.1, 1, 10, 100} in Nano seconds. The power dissipation in micro watts P= {0.01, 0.1, 1, 10, 100} Develop the fuzzy relation between logic families and power dissipation. [16] 3. How to generate membership function by using Genetic Algorithms? [16] 4. For the function y = 2 2 - 3 1 + 4 , where the membership functions for fuzzy 1+2 variables X1 , X2 shown in Figure 4: nd and plot the membership function for the fuzzy out put variable , y , using the DSW algorithm. [16] Figure 4 5. v3 is not a rational number; i.e., show that it can not be the ratio of two even integers by contradiction? [16] 6. A factory process control operation involves two linguistic (atomic) parameters consisting of pressure and temperature in a uid delivery system. Nominal pressure limits range from 400 psi maximum. Nominal temperature limits are 1300F to 1400F. We characterize each parametre in fuzzy linguistic terms as follows:
  4. 4. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 2 “”=1 131 + 0132 + 0133 + 0134 + 0135 + 0136 8 6 4 2 “”=0 134 + 0135 + 0136 + 0137 + 0138 + 1139 2 4 6 8 “”=0 400 + 0600 + 0700 + 0800 + 0900 + 11000 2 4 6 8 “”=1 400 + 0600 + 0700 + 0800 + 0900 + 01000 8 6 4 2 Find the following membership functions (a) Temperature not very low. (b) Temperature not very high. (c) Temperature not very low & not very high. [16] 7. Write a notes on decision making under fuzzy states and fuzzy actions? [16] 8. A fuzzy tolerance relation. R. is re exive and symmetric. Find the equivalence relation R and then classify it according to -cut levels ={0.9,0.8,0.5}. 10800201 08109004 = 0091003 [16] 0200105 010403051
  5. 5. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 3 IV B.Tech II Semester Regular Examinations, Apr/May 2007 FUZZY LOGIC AND APPLICATION (Electrical & Electronic Engineering) Time: 3 hours Max Marks: 80 Answer any FIVE Questions All Questions carry equal marks 1. Propose membership functions to describe ‘a fuzzy resister’ with a nominal value of 1M and another one of 5.6k . [16] 2. In DC motor speed control under no load condition, generally the external series resistance in armature Rse should be kept in cut in position. For example in ar- mature controlled method the ux maintained at some constant value; then motor speed is proportional to back e.m.f. (a) What should be the minimum and maximum level of Rse ? (b) What should be the minimum and maximum level of Ia? Rse= Rs1, Rs2, Rs3 Rsn Ia= I1, I2, I3 Im N= N1,N2,N3NV Where Rse, Ia, N, are fuzzy sets of armature series resistance, armature current, Speed respectively. The membership functions for above for given in terms of Percentage of respective rated values. Rse = 0.3 30 + 0.7 60 + 1.0100 + 0.2120 Ia = 0.2 20 + 0.4 40 + 0.6 60 + 0.8 80 + 1.0 100 + 0.1120 = 0.33 500 + 0.67 1000 + 1.01500 + 0.15 1800 R=Rse Ia; S=N Ia Find max-min composition for T=R S. [16] 3. Using your own institution, develop fuzzy membership functions on the real line for the fuzzy numbers 3, using the following function shapes; (a) Symmetric triangle (b) Trapezio d (c) Gaussian function. [16] 4. Explain Center of Sums, Center of Largest Area Defuzzifying Methods? [16] 5. Show that the dual of equivalence ( ) is also true? [16] 6. Using the image processing techniques, suppose you are trying to locate object or shapes within an image eld. An object is big or small according to whether it has a value above or below a prede ned threshold based on the number of consecutive pixel elds in a row - column image matrix. De ne a universe of discourse of the number of adjacent pixels above a certain threshold on the interval [50, 300], then,
  6. 6. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 3 for the membership function for “big” and “small,” “”=0 50 + 0100 + 0150 + 0200 + 0250 + 1300 2 3 8 9 “”=1 50 + 0100 + 0150 + 0200 + 0250 + 0300 5 1 De ne the membership function for the following three linguistic expression: (a) Not big and very small (b) Very, very big or not small (c) Not very, very big. [16] 7. Write a short note on multi stage decision making? [16] 8. Write step by step procedure C - Means Algorithm? [16]
  7. 7. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 4 IV B.Tech II Semester Regular Examinations, Apr/May 2007 FUZZY LOGIC AND APPLICATION (Electrical & Electronic Engineering) Time: 3 hours Max Marks: 80 Answer any FIVE Questions All Questions carry equal marks 1. Let the fuzzy sets A, B and C be the sub sets of the universe {1,2,3??., 199,200}. Let A= {1/0.1, 2/0.3,3/0.3, 4/0.4, 5/0.5, 6/0.7, 7/0.8, 8/0.9, 9/1, 10/1} and B= {1/0.1, 2/0.3, 3/0.5, 4/0.7, 5/0.9, 6/1,7/0.8, 8/0.5, 9/0.2, 10/0}. Find out the fuzzy sets C= A*(A+B); C= A2; C= 1/B. [16] 2. The matrix expression for the crisp relation by using max-min composition opera- tion The relation matrices for R & S would be expressed as 1 0 1 0 1 2 3 4 1 0 21 1 =1 2 00 Find max-min composition? 2 3 0 0 0 1 And = 3 01 0 0 0 0 4 00 [16] 3. Classify all possible hedges? And Explain with suitable meaning? [16] 4. For the function y = 2 2 - 3 1 + 4 , where the membership functions for fuzzy 1+2 variables X1 , X2 shown in Figure 4: nd and plot the membership function for the fuzzy out put variable , y , using A discretized form of the extension principle. [16] Figure 4 5. Explain about classical predicate logic connectives? [16] 6. What are the di erent linguistic hedges and how the linguistic hedges have the e ect of modifying the membership function basic atomic term ? [16] 7. When evaluating expert system to ols, four evaluation criteria are used: (a) Excellent (b) good
  8. 8. www.studentyogi.com www.studentyogi.com Code No: RR420208 Set No. 4 (c) Fair and (d) Mediocre. There are four aspects: I / O facilities, debugging aids, knowledge based editors, and explanation facilities. The following table shows relationship matrix. Excellent good fair mediocre I/O 0.3 0.4 0.2 0.1 Debug 0.2 0.5 0.3 0 Editors 0.5 0.2 0.2 0.1 Explain 0.1 0.6 0.2 0.1 Suppose we have weight factor ~ = {0.2, 0.4, 0.3, 0.1}, Evaluate the expert system tool. [16] 8. A customer evaluates ve banks by their mortgage policy, loan interest, and div- idend bene ts. She has developed a fuzzy tolerance relation R according to these three criteria for banks. If she uses a -cut level of 0.8, then how many classes can she make from these banks? 102050907 021060408 = 050610403 [16] 090404105 070803051

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