Steps for Hybrid Intelligent Algorithm

The process for the hybrid intelligent algorithm is illustrated in Fig. 6.2, the detailed steps are shown as following  

Determine and input the pop size, crossover probability Pc, mutation probability P, termination generations max gen and initial generations 1 = 0. 

Generate the input and output data for uncertain function using fuzzy stochastic simulation (training samples). 

Approach the uncertain function training three-layer feedforward neural networks using the generated input and output data. 

Update the chromosome using crossover and mutation processes and check the feasibility of the offspring chromosome using well trained neural network. 

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The termination condition is determined by the max gen. If timplement Step 5-Step 8 in the Steps for hybrid intelligent algorithm (in Sect. 6.3.5). The algorithm ends when t = max gen. 

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