cia-assgn1-201516

EIE557 Computational Intelligence and Its ApplicationsAssignment 1 (due on 22 October 2015) Q1. Discuss the difference between expert systems and artificial neural networks. Q2. Explain the main advantages of applying fuzzy logic in knowledge-based systems. Q3. The Zookeeper expert system was developed to identify seven animals: a cheetah, a tiger, a giraffe, a zebra, an ostrich, a penguin, and an albatross. The system has 15 production rules given below: R1 R4 IF THEN IF THEN IF THEN IF R5 THEN IF R6 THEN IF R7 THEN IF R8 THEN IF R9 THEN IF R10 THEN IF R11 THEN IF R2 R3 THEN ?x has hair ?x is a mammal ?x gives milk ?x is a mammal ?x has feathers ?x is a bird ?x flies ?x lays eggs ?x is a bird ?x is a mammal ?x eats meat ?x is a carnivore ?x is a mammal ?x has pointed teeth ?x has claws ?z has forward-pointing eyes ?x is a carnivore ?x is a mammal ?x has hoofs ?x is an ungulate ?x is a mammal ?x chews cud ?x is an ungulate ?x is a carnivore ?x has tawny color ?x has dark spots ?x is a cheetah ?x is a carnivore ?x has tawny color ?x has black strips ?x is a tiger ?x is an ungulate ?x has long legs ?x has long neck ?x has tawny color ?x has dark spots ?x is a giraffe 1  Splashy is black and white. Indicate your answer by showing what is the sequence in which the rules are used. and whether each rule succeeds. Assume that nothing else is known to be true. consider the following facts about an animal.  Splashy does not fly. Splashy:  Splashy has feathers. The following rules are given: R1: IF ?x is a bird ?x does not fly ?x has long legs ?x has long neck ?x is black and white 2 . (b) Rework the exercise in the previous part assuming that Splashy has long legs and a long neck.R12 IF R13 THEN IF R14 THEN IF R15 THEN IF THEN ?x is an ungulate ?x has white color ?x has black stripes ?x is a zebra ?x is a bird ?x does not fly ?x has long legs ?x has long neck ?x is black and white ?x is an ostrich ?x is a bird ?x does not fly ?x swims ?x is black and white ?x is a penguin ?x is a bird ?x is a good flyer ?x is an albatross Assume that the Zookeeper procedure is asked to chain backward from the following hypotheses in the given order: Ostrich Penguin Albatross Then.  Splashy lays eggs. Why is the result peculiar? Q4. The other properties are unchanged.  Splashy swims. what each rule is trying to do. (a) Simulate Zookeeper’s behavior so as to determine what kind of animal Splashy is. Take care to use the hypotheses in the specified order. 8}.THEN ?x is an ostrich with a certainty factor of 0. Splashy:  Splashy has feathers {cf 0. 3 . Figure Q5 shows the membership functions for fuzzy sets A and B. R2: IF ?x has feathers THEN ?x is a bird with a certainty factor of 0.  Splashy has long legs {cf 0.” Q5. (b) Find the union and intersection of fuzzy sets A and B using the max and min operators.  Splashy lays eggs {cf 0.9.9.” (b) Compute the certainty factor of the conclusion “Splashy is an ostrich.8}. (a) Compute the certainty factor of the assertion “Splashy is a bird.  x  1.6}  Splashy has long neck {cf 0. R3: IF ?x flies ?x lays eggs THEN ?x is a bird with a certainty factor of 0.0 -4 -1 O A B x 1 3 4 6 Figure Q5 (a) Derive  A x  and  B x  as mathematical equations.0}. Consider the following facts about an animal.8. 1].  Splashy is black and white {cf 1.4}.6}. Illustrate the membership functions and give the mathematical equations for  AB x  and  AB x  . The range of certainty factors is [-1. respectively.  Splashy does not fly {cf 0. 6  N de   0.0 Figure Q6 (a) Find the firing strength for each rule if the min operator is utilized for the AND operation.0 -1. (c) Use (i) the middle-of-maximum method and (ii) the center-of-maxima method to obtain the crisp output y.  P de   0.5 y N 1. N (negative) with the membership functions shown in Figure Q6.0 2.4. Z (zero). It has four rules: R1: if e = P and de = P then y = N R2: if e = P and de = N then y = Z R3: if e = N and de = P then y = Z R4: if e = N and de = N then y = P There are two fuzzy sets for each of input variables e and de: P (positive) and N (negative).0 Z P y -2. 4 . Show the combined output fuzzy set if the max operator is utilized to aggregate the output fuzzy sets produced by the fired fuzzy rules.Q6.  P e   0.5.0 0 1. (b) Assume that the min operator is used for the implication process. The output fuzzy variable y has three values: P (positive). A simple controller uses an error signal e and the change in the error signal de as inputs. Assume that the input variables have the following membership degrees in the input fuzzy sets:  N e   0. Discuss the pros and cons of a large population size. (a) Complete the missing columns of the table. “selection probability” and “accumulated probability”. 0.37. how can we ensure that a large part of the search space is covered? Q8.17. 0. 0. What individuals will be selected using the roulette wheel selection? Individual Chromosome Table Q9 Fitness Selection probability. 0. 0.85.78. In the case of a small population size. Use a genetic algorithm to find a solution to the following problem: x 2  64.29.54. solve for x.27.45. (1) Discuss the solution (chromosome) representation.51. Table Q9 shows a population of 10 individuals with their fitness values.Q7. (2) Propose a sound fitness function for the problem.070. 0. 0. 0. (b) Assume that the following random number sequence is generated: 0. 0. fi Pi 8 5 9 1 2 3 0001100000 0101111001 0000000101 4 1001110100 10 5 6 1010101010 1110010110 17 6 7 8 9 10 1001011011 1100000001 1001110100 0001010011 15 19 10 14 5 Accumulated probability . Q9. crossover and mutation operators for the problem. (3) Suggest the selection. 6 . 4. 5. 3 6. 2. 5 Fitness 100 200 300 400 450 550 (a) Determine each individual’s probability of being selected as a parent if the tournament selection of k  2 is used (two distinct individuals selected randomly with uniform probability compete in any tournment).Q10. 1 3. 2. (b) If individuals 5 and 6 are selected as parents for the one-point crossover. The initial population of 6 individuals are shown in Table Q10. 3. 2. 1. 3 2. 4. 2. Individual 1 2 3 4 5 6 Table Q10 Genotype 2. 3. Consider a genetic algorithm using chromosomes represented by a vector of 4 integers. list the genotypes of all children that may be produced. 3 5. 4. 2 3. 2. 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