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Recognition of Mixture Control Chart Pattern Using Multiclass Support Vector Machine and Genetic Algorithm Based on Statistical and Shape Features

机译：基于统计和形状特征的多标准支持向量机和遗传算法识别混合控制图图案

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摘要

Control charts have been widely utilized for monitoring process variation in numerous applications. Abnormal patterns exhibited by control charts imply certain potentially assignable causes that may deteriorate the process performance. Most of the previous studies are concerned with the recognition of single abnormal control chart patterns (CCPs). This paper introduces an intelligent hybrid model for recognizing the mixture CCPs that includes three main aspects: feature extraction, classifier, and parameters optimization. In the feature extraction, statistical and shape features of observation data are used in the data input to get the effective data for the classifier. A multiclass support vector machine (MSVM) applies for recognizing the mixture CCPs. Finally, genetic algorithm (GA) is utilized to optimize the MSVM classifier by searching the best values of the parameters of MSVM and kernel function. The performance of the hybrid approach is evaluated by simulation experiments, and simulation results demonstrate that the proposed approach is able to effectively recognize mixture CCPs.

机译：控制图已被广泛用于监视许多应用中的过程变化。控制图表呈现的异常模式意味着某些可能导致的可能导致过程性能恶化。以前的大多数研究涉及识别单一异常控制图表模式（CCP）。本文介绍了一种智能混合模型，用于识别包括三个主要方面的混合CCP：特征提取，分类器和参数优化。在特征提取中，在数据输入中使用观察数据的统计和形状特征以获取分类器的有效数据。多键支持向量机（MSVM）适用于识别混合物CCP。最后，利用遗传算法（GA）来通过搜索MSVM和内核函数的参数的最佳值来优化MSVM分类器。通过仿真实验评估混合方法的性能，仿真结果表明，所提出的方法能够有效地识别混合CCP。

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Min Zhang; Wenming Cheng;
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年度 2015
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正文语种 eng
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专利

1. Recognition of Mixture Control Chart Pattern Using Multiclass Support Vector Machine and Genetic Algorithm Based on Statistical and Shape Features [J] . Zhang Min, Cheng Wenming Mathematical Problems in Engineering . 2015,第PTa19期

机译：基于统计和形状特征的多类支持向量机和遗传算法的混合控制图模式识别
2. Recognition of Mixture Control Chart Pattern Using Multiclass Support Vector Machine and Genetic Algorithm Based on Statistical and Shape Features [J] . MinZhang, WenmingCheng Mathematical Problems in Engineering: Theory, Methods and Applications . 2015,第5期

机译：基于统计和形状特征的多类支持向量机和遗传算法的混合控制图模式识别
3. Recognition of Mixture Control Chart Pattern Using Multiclass Support Vector Machine and Genetic Algorithm Based on Statistical and Shape Features [J] . MinZhang, WenmingCheng Mathematical Problems in Engineering: Theory, Methods and Applications . 2015,第5期

机译：基于统计和形状特征的多类支持向量机和遗传算法的混合控制图模式识别
4. Recognition of control chart patterns using genetic algorithm and support vector machine [C] . International Conference on Networked Digital Technologies . 2009

机译：使用遗传算法和支持向量机识别控制图表模式
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Recognition of Mixture Control Chart Pattern Using Multiclass Support Vector Machine and Genetic Algorithm Based on Statistical and Shape Features

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