Abstract
The data of process parameters and quality index from CAE simulation orthogonal test is used as training samples, the BP neural network is trained and the neural networks ensemble approximate calculation agent model of the relations between processing parameters and the quality index of product are obtained. The agent model with a clear mathematical formula calculates quickly and accurately, so it can optimize globally by the genetic algorithm. The best group of process parameters is obtained and a multi-objective optimization of the quality index of products is realized.
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