Title :
The Improved Transductive Support Vector Machine and Its Application to Environment Monitoring in Industrial Seaculture
Author :
Man-fu, Yan ; Zhao-xia, Wang
Author_Institution :
Dept. of Math., Tangshan Teachers´´ Coll., Tangshan, China
fDate :
March 31 2009-April 2 2009
Abstract :
The study on Transductive Support Vector Machine(TSVM) has made little progress since Vapnik put forth the concept in the late 1990s, as algorithm for TSVM optimization model can not be easily found. Here we try to transform the problem of TSVM optimization into an unconstrained one before constructing the smooth unconstrained optimization that has a kernel, and on the basis of which to devise a TSVM whose optimization problem is easier to solve to breakthrough the bottleneck in order to deepen the research into TSVM and apply TSVM to environment monitoring of industrial sea culture.
Keywords :
aquaculture; environmental factors; support vector machines; TSVM optimization model; environment monitoring; industrial seaculture; smooth unconstrained optimization; transductive support vector machine; Application software; Computer industry; Computer science; Computerized monitoring; Condition monitoring; Educational institutions; Kernel; Mathematical model; Mathematics; Support vector machines; Environment Monitoring; Optimization; Smoothing Function; Transductive Support Vector Machine; Unconstrained;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.58