Support vector machine-based method for quality characteristic modeling

被引:0
|
作者
Liu, J. [1 ]
Xu, L. J. [1 ]
Lin, Z. H. [1 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710049, Peoples R China
关键词
root-cause identification; quality characteristic modeling; Support Vector Machine (SVM);
D O I
10.4028/www.scientific.net/AMM.10-12.253
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Root-cause identification and product quality characteristic modeling are key issues for improving product quality and the productivity of manufacturing process. The quality characteristic model, which indicates the influence of the dominate root-causes on the product quality characteristic, is the basis for quality control. In this paper an approach for quality characteristic modeling based on Support Vector Machine is presented. The selections of parameters and the Kernel function are discussed. The presented approach is applied for analyzing and predicting the quality of inertial gyroscope.
引用
收藏
页码:253 / +
页数:2
相关论文
共 50 条
  • [21] Support vector machine-based similarity selection method for structural transient reliability analysis
    Chen, Jun-Yu
    Feng, Yun-Wen
    Teng, Da
    Lu, Cheng
    Fei, Cheng-Wei
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, 223
  • [22] Support vector machine-based text detection in digital video
    Shin, CS
    Kim, KI
    Park, MH
    Kim, HJ
    NEURAL NETWORKS FOR SIGNAL PROCESSING X, VOLS 1 AND 2, PROCEEDINGS, 2000, : 634 - 641
  • [23] Support vector machine-based hysteresis model of piezoelectric actuator
    Yan X.
    Wu H.
    Li Y.
    Yang X.
    Kang S.
    Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2018, 39 (09): : 228 - 235
  • [24] Forecasting Volatility with Support Vector Machine-Based GARCH Model
    Chen, Shiyi
    Haerdle, Wolfgang K.
    Jeong, Kiho
    JOURNAL OF FORECASTING, 2010, 29 (04) : 406 - 433
  • [25] An improved support vector machine-based diabetic readmission prediction
    Cui, Shaoze
    Wang, Dujuan
    Wang, Yanzhang
    Yu, Pay-Wen
    Jin, Yaochu
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2018, 166 : 123 - 135
  • [26] Support vector machine-based fuzzy rules acquisition system
    Huang X.-X.
    Shi F.-H.
    Gu W.
    Chen S.-B.
    Journal of Shanghai Jiaotong University (Science), 2009, 14 (05) : 555 - 561
  • [27] A Support Vector Machine-Based Genetic AlgorithmMethod for Gas Classification
    Wang, Kun
    Ye, Wenbin
    Zhao, Xiaojin
    Pan, Xiaofang
    2017 2ND INTERNATIONAL CONFERENCE ON FRONTIERS OF SENSORS TECHNOLOGIES (ICFST), 2017, : 363 - 366
  • [28] Support Vector Machine-based Fuzzy Rules Acquisition System
    黄细霞
    石繁槐
    顾伟
    陈善本
    Journal of Shanghai Jiaotong University(Science), 2009, 14 (05) : 555 - 561
  • [29] Support Vector Machine-based Soft Sensors in the Isomerisation Process
    Herceg, S.
    Andrijic, Z. Ujevic
    Bolf, N.
    CHEMICAL AND BIOCHEMICAL ENGINEERING QUARTERLY, 2020, 34 (04) : 243 - 255
  • [30] TMPpred: A support vector machine-based thermophilic protein identifier
    Meng, Chaolu
    Ju, Ying
    Shi, Hua
    ANALYTICAL BIOCHEMISTRY, 2022, 645