基于数据挖掘的工艺参数优化研究

Research on the Optimization of Process Parameters Based on DataMining

提出了基于数据挖掘的机械加工工艺参数寻优方法,根据已有的样本训练数据建立决策树分类器和神经网络模型,针对要求的加工目标,通过对决策树的分类规则进行提取,生成预测数据集,结合建立的神经网络模型,迅速准确的预测出对应的加工工艺参数,并通过磨削实验验证了此方法的可行性。

The paper introduces a kind of optimizining method of mechanical process parameters based on Decision Tree Classifier and Neural Networks. Training data with the sample,the model of the classifier and Neural Networks can be built. To satisfy the machining request,using these two models to deal with the data set, proper process parameters can be forecaste.