Soft-sensor modeling method based on support vector machines | |
Zhang, MG; Yan, WW | |
2005 | |
关键词 | soft-sensor modeling support vector machines |
页码 | 208-213 |
英文摘要 | Soft-sensor has been widely used in industrial process control to improve the quality of product and assure safety in production. The core problem of soft-sensor is to construct appropriate mathematic model. Support vector machines (SVM) is a novel machine learning method based on structure risk minimizing principle, which is powerful for the problem characterized by small sample, nonlinearity, high dimension and local minima, and has high generalization. In this paper, soft-sensor modeling method and algorithm based on Support Vector Machines (SVM) is proposed, and cross validation method is used to select hyper-parameters of SVM model. Soft-sensor model based on SVM is applied to estimation nonlinear time-vary system. Experiment results show that SVM provides a new effective method for soft-sensor modeling and has promising application in industrial process applications. |
会议录 | ICEMI 2005: CONFERENCE PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL 7
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会议录出版者 | INTERNATIONAL ACADEMIC PUBLISHERS LTD |
会议录出版地 | UNIT 1205, 12 FLOOR, SINO PLAZA, 255 GLOUCESTER ROAD, HONG KONG 00000, CAUSEWAY BAY, PEOPLES R CHINA |
语种 | 英语 |
WOS研究方向 | Engineering ; Instruments & Instrumentation |
WOS记录号 | WOS:000235128600045 |
内容类型 | 会议论文 |
源URL | [http://119.78.100.223/handle/2XXMBERH/38345] ![]() |
专题 | 电气工程与信息工程学院 |
通讯作者 | Zhang, MG |
作者单位 | Lanzhou Univ Technol, Sch Elect & Informat Engn, Lanzhou 730050, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, MG,Yan, WW. Soft-sensor modeling method based on support vector machines[C]. 见:. |
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