What is the feature of ANNs due to which they can deal with noisy, fuzzy, inconsistent data?

Related MCQs

• What is the feature of ANNs due to which they can deal with noisy, fuzzy, inconsistent data?
• Choose the correct statement 1. A fuzzy set is a crisp set but the reverse is not true 2. If A,B and C are three fuzzy sets defined over the same universe of discourse such that A ≤ B and B ≤ C and A ≤ C 3. Membership function defines the fuzziness in a fuzzy set irrespecive of the elements in the set, which are discrete or continuous
• Choose the correct statement 1. A fuzzy set is a crisp set but the reverse is not true 2. If A,B and C are three fuzzy sets defined over the same universe of discourse such that A ≤ B and B ≤ C and A ≤ C 3. Membership function defines the fuzziness in a fuzzy set irrespecive of the elements in the set, which are discrete or continuous
• Who can deal with noisy input information
• Identify the drawbacks of clustering algorithms? 1) can geneerate empty clusters 2) can terminate at local minimum 3)can handle noisy data
• Compute the value of adding the following two fuzzy integers: A = {(0.3,1), (0.6,2), (1,3), (0.7,4), (0.2,5)} B = {(0.5,11), (1,12), (0.5,13)} Where fuzzy addition is defined as μA+B(z) = maxx+y=z (min(μA(x), μB(x))) Then, f(A+B) is equal to
• The height h(A) of a fuzzy set A is defined as h(A)=support A(x), where A belongs to A. Then fuzzy set is called normal when
• The height h(A) of a fuzzy set A is defined as h(A) =sup A(x) where x belongs to A. Then the fuzzy set A is called normal when
• Compute the value of adding the following two fuzzy integers: A = {(0.3,1), (0.6,2), (1,3), (0.7,4), (0.2,5)} B = {(0.5,11), (1,12), (0.5,13)} Where fuzzy addition is defined as μA+B(z) = maxx+y=z (min(μA(x), μB(x))) Then, f(A+B) is equal to
• Which of the following algorithm is most efficient for discotinuous and noisy problems?