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Customer preferences Fuzzy Clustering based dynamic multivariate process quality control method

机译：客户首选项基于模糊聚类的动态多变量过程质量控制方法

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Jingping Yang; Wanlei Wang; Shikuan Zhou; Bin Wu;
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年度 2016
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1. A New Method for Short Multivariate Fuzzy Time Series Based on Genetic Algorithm and Fuzzy Clustering [J] . Kamal S.Selim, Gihan A.Elanany Advances in fuzzy systems . 2013,第5期

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2. Monitoring Hole Quality in a Drilling Process Using a Fuzzy Subtractive Clustering-Based System Identification Method [J] . Mohammed T. Hayajneh, Saleh. M. Radaideh Journal of testing and evaluation . 2007,第3期

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3. Fuzzy Clustering Methods for Categorical Multivariate Data Based on q-Divergence [J] . Tadafumi Kondo, Yuchi Kanzawa Journal of Advanced Computatioanl Intelligence and Intelligent Informatics . 2018,第4a131期

机译：基于Q分歧的分类多变量数据模糊聚类方法
4. Customer preferences Fuzzy Clustering based dynamic multivariate process quality control method [C] . Jingping Yang, Wanlei Wang, Shikuan Zhou, International Conference on Sensors, Measurement and Intelligent Materials . 2016

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5. Fault Identification in Multivariate Processes Using the Analysis of Multiple Univariate Statistical Quality Control Charts Along With T2 Multivariate Quality Control Charts Based on the Effect of the Underlying Variances and Covariances [D] . Alothman, Hussam Ali. 2019

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8. Management Methods for Quality Improvement Based on Statistical Process Control: A Literature and Field Survey [R] . Houston, A., Shettel-Neuber, J., Sheposh, J. P. 1986

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Customer preferences Fuzzy Clustering based dynamic multivariate process quality control method

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