Title :
Decision of the mechanical drive type with fuzzy characters based on the support vector machine
Author :
Sun, Hua-li ; Xie, Jian-Ying ; Xue, Yao-feng
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., China
Abstract :
An overview of the basic idea underlying support vector machine (SVM) is given, and then a multi-object classifier through one-against-all algorithm is formulated. A novel method of the support vector machines (SVMs) applied to the decision of mechanical drive type with fuzzy characters is discussed firstly. The results prove that SVM can provide a fast and effective method for engineering.
Keywords :
drives; fuzzy set theory; pattern classification; support vector machines; SVM; fuzzy characters; mechanical drive; multiobject classifier; one-against-all algorithm; support vector machine; Automation; Computer vision; Drives; Electronic mail; Machine learning; Neural networks; Quadratic programming; Sun; Support vector machine classification; Support vector machines;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1378580
