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| (i) Decode each individual in the current population into a set of connection weights and construct a corresponding ANN with the weights. | |
| (ii) Evaluate the ANN by computing its total mean square error between actual and target outputs. | |
| (iii) Determine fitness of individual as inverse of error. The higher is the error, the lower is the fitness. | |
| (iv) Store the weights for mating pool formation. | |
| (v) Implement search operators such as cross-over/mutation to parents to generate offsprings. | |
| (vi) Calculate fitness for new population. | |
| (vii) Repeat steps (iii) to (vi) until the solution converge. | |
| (viii) Extract optimized weights. | |
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