首页> 外文会议>IFIP 207; IFIP(International Federat; ; >PREDICTING ASSEMBLY QUALITY OF COMPLEX STRUCTURES USING DATA MINING-Predicting with Decision Tree Algorithm
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PREDICTING ASSEMBLY QUALITY OF COMPLEX STRUCTURES USING DATA MINING-Predicting with Decision Tree Algorithm

机译:数据挖掘预测复杂结构的装配质量-决策树算法预测

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摘要

Our research aims at obtaining the relevant factors that cause the decrease in quality of assembly parts. Decision tree technique was employed to induce useful information hidden within a vast collection of data. The major objective of this study was to classify the existing data into certain types of segmentations and then predict the behaviour of a ball joint assembly. The intervals of the rolling time and achieved rolling force leading to occurrence of the high moment values of the ball joint during testing stage have been found.
机译:我们的研究旨在获得导致装配零件质量下降的相关因素。决策树技术被用来诱导隐藏在大量数据中的有用信息。这项研究的主要目的是将现有数据分类为某些类型的细分,然后预测球形接头组件的行为。已发现导致测试阶段球窝关节出现高力矩值的滚动时间间隔和所获得的滚动力。

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