• DocumentCode
    630525
  • Title

    The research on application of sliding window LS_SVMin the batch process

  • Author

    Xin Sun ; Xue Jin gao ; Zhi Yang jia

  • Author_Institution
    Coll. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    292
  • Lastpage
    295
  • Abstract
    This paper presents an improved regression algorithm of sliding window least squares support vector machine (the Sliding Window LS_SVM). This method simplifies the data within the sliding window, and selects the similar data for local modeling from a database of historical batches to predict the data within the sliding window. Combined with local modeling, the improved sliding window LS_SVM algorithm is very effective to predict the cell concentration in the penicillin fermentation process.
  • Keywords
    batch processing (industrial); fermentation; regression analysis; batch process; penicillin fermentation proces; regression algorithm; sliding window least squares support vector machine; Adaptation models; Batch production systems; Data models; Databases; Predictive models; Support vector machines; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6579852
  • Filename
    6579852
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=630525