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论述了人工神经网络和遗传算法在塑料热压成型工艺优化中的应用,首先利用人工神经网络建立热压成型工艺参数与零件性能之间关系的数学模型,然后用遗传算法对工艺参数优化。根据多目标函数优化问题的单目标化思想,对优化后的单目标进行分解,得到最优工艺参数条件下的塑料热压产品性能,从而为建立和控制塑料热压成型工艺参数提供了一种行之有效的方法。
The application of artificial neural network and genetic algorithm in plastic thermoforming process optimization is discussed. First, the artificial neural network is used to establish the mathematical model of the relationship between thermoforming process parameters and part performance, and then the genetic algorithm is used to optimize the process parameters. According to the single-objective idea of multi-objective function optimization problem, the optimized single objective is decomposed to obtain the properties of plastic hot pressing products under the optimal process parameters, thus providing a method for establishing and controlling the plastic hot pressing forming process parameters Effective method.