For a universal set X = {a, b, c, d, e) of 5 kinds of features, Basic probability assignments (BPA) of evidence are given by a sensor A, as follows: mA({a})= 0.3, m({a, b})= 0.2, m₁({a, b, c)) = 0.3, mA(X) = 0.2 Here, another sensor B independently has a different body of evidence, mg({b})= 0.5, mg({a, b, c)) = 0.3, mg(X) = 0.2
For a universal set X = {a, b, c, d, e) of 5 kinds of features, Basic probability assignments (BPA) of evidence are given by a sensor A, as follows: mA({a})= 0.3, m({a, b})= 0.2, m₁({a, b, c)) = 0.3, mA(X) = 0.2 Here, another sensor B independently has a different body of evidence, mg({b})= 0.5, mg({a, b, c)) = 0.3, mg(X) = 0.2
Chapter8: Sequences, Series,and Probability
Section8.7: Probability
Problem 4ECP: Show that the probability of drawing a club at random from a standard deck of 52 playing cards is...
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The membership function of a discrete fuzzy set is shown as fallow 1) Find ‘alpha-cut’s of the fuzzy set using crisp interval sets, A(alpha)= [x1,x2] 2) Use the ‘resolution identity’ in order to represent this fuzzy subset with A(alpha)
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