Generate the population in the next iteration by using Roulette-Wheel criterion:
| k | Fk |
| 1 | 3.5 |
| 2 | 4.6 |
| 3 | 5 |
| 4 | 2.8 |
| 5 | 1.8 |
Soft Computing is a multidisciplinary field that encompasses various computational techniques inspired by nature, human cognition, and biological systems. One of the widely used techniques in soft computing is the Genetic Algorithm (GA), which involves the creation of a population and _______ ___ _________ ________ __________ _______ _______.
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Implement AND function using McCulloch-Pitts neuron.
Consider the single layer perception given below:
Obtain the output for each of the following input pattern:
| Patterns | p1 | p2 | p3 | p4 |
| x1 | 1 | 0 | 1 | 1 |
| x2 | 0 | 1 | 0 | 1 |
| x3 | 0 | 1 | 1 | 1 |
Verify whether the Genetic Algorithm (GA) improves the solution from one generation to the next generation, for the function given below:
Maximize:
f(x) =
Subject to:
1≤ x ≤16
Assume that chromosomes of length 6 are created at random and modified by Roulette-Wheel selection.
Generate the population in the next iteration by using Roulette-Wheel criterion:
| k | Fk |
| 1 | 3.5 |
| 2 | 4.6 |
| 3 | 5 |
| 4 | 2.8 |
| 5 | 1.8 |
Consider a dataset of five observations given in the following table, each of which has two features f and f 2:
Assume the number of cluster c = 3 and the real number m = 2 . Also, assume the initial cluster centers as V )1,1( 1 = and V )2,2( 2 = . Apply fuzzy c-mean algorithm to find the modified cluster center after one iteration.
Solve the network to approximate the function:
g(x)=1+sin
for −1≤ x ≤ ,1 choosing the initial weights and bias as the random numbers.
Consider the ADALINE filter with three neurons in the input layer having weights 1,3 and − 2and the input sequence ......., ,0,0,0 − 0,0,0,5,4 ,.....}. Find the filter output.