The research on application of sliding window LS-SVMin the batch process

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2013 American Control Conference, ACC 2013
Pages292-295
Number of pages4
Publication statusPublished - 2013
Externally publishedYes
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: 17 Jun 201319 Jun 2013

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2013 1st American Control Conference, ACC 2013
Country/TerritoryUnited States
CityWashington, DC
Period17/06/1319/06/13

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