基于机器学习的制造系统分类

T. Witkowski, P. Antczak, A. Antczak
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引用次数: 9

摘要

本文介绍了归纳学习在制造系统知识获取中的应用。该模型的软件使我们能够分析反映各种组合其他因素的许多变体的过程构建规则。为生成机器学习算法所需的训练示例而选择的一组属性已被使用。实验表明,这些方法非常适合于制造问题的分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning — Based classification in manufacturing system
This paper shows the application of inductive learning for acquisition of knowledge in manufacturing system. The software of this models, allows us to analyze the process construction rules for many variants reflecting a variety of combinations other factors. A sets of attributes selected for generating the necessary training examples for the machine learning algorithm have been used. Experiments indicate that these methods are well suited to do the classification of manufacturing problems.
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