Prediction Algorithm of Trim Beam Number Using Modified SVM-Based Feature Selection

doi:10.13190/jbupt.200906.88.sunyp

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2009, Vol. 32 ›› Issue (6): 88-92.doi: 10.13190/jbupt.200906.88.sunyp

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Prediction Algorithm of Trim Beam Number Using Modified SVM-Based Feature Selection

SUN Yue-peng;LIU Min;HAO Jing-hua;WU Cheng

(1. Department of Automation, Tsinghua University, Beijing 100084, Chin
a;2. National CIMS Engineering Research Center, Tsinghua University, Beijing 100084, China)

Received:1900-01-01 Revised:1900-01-01 Online:2009-12-28 Published:2009-12-28
Contact: SUN Yue-peng

Abstract

Abstract:

The trim beam number is an important parameter in the scheduling model of the cotton spinning manufacturing process. Because of the complexity of the trim technique, the actual trim beam number is difficult to obtain before scheduling. A prediction algorithm using a modified support vector machine (SVM)-based feature selection method and feed forward neural network (FFNN) is presented for predicting the trim beam number. In the algorithm, the proposed feature selection method is adopted to pick up critical features that affect the trim beam number, and FFNN is adopted to predict the trim beam number based on the critical features. Numerical computational results show that the proposed algorithm is effective. The algorithm also successfully applies in the related problems in practical cotton textile manufacturing system.

Key words: support vector machine, trim beam number, feature selection, prediction, scheduling

SUN Yue-peng;LIU Min;HAO Jing-hua;WU Cheng. Prediction Algorithm of Trim Beam Number Using Modified SVM-Based Feature Selection[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2009, 32(6): 88-92.

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Prediction Algorithm of Trim Beam Number Using Modified SVM-Based Feature Selection

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