半导体工业事故研究:基于BP人工神经网络的预测

2013 IEEE International Conference on Industrial Engineering and Engineering Management Pub Date : 2013-12-01 DOI:10.1109/IEEM.2013.6962460

L. Chao, Hsu PeiChen, Wu Jianping

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引用次数: 2

摘要

本文提出利用BP人工神经网络对半导体行业事故进行预测，以优化的、可量化的事故影响因子作为输入节点，以事故数量作为输出节点。所建立的预测模型有7个输入参数和1个输出参数。本文利用该模型对某半导体公司的事故发生情况进行了预测和验证，得到了准确的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A study of semiconductor industry accidents: Making predictions based on BP artificial neural networks

This paper puts forward using BP artificial neural network to forecast semiconductor industry accidents, using optimized and quantifiable impact factors of accidents as input nodes and accident quantity as the output node. The established predictive model has 7 input parameters and 1 output parameter. This paper uses this model to predict and validate the accident occurrence circumstances of a semiconductor company and gets accurate results.

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2013 IEEE International Conference on Industrial Engineering and Engineering Management

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