Online Modeling Based on Support Vector Machine
Support vector machine (SVM) is a new method based on statistical learning theory. Online algorithms for training SVM are efficient to run, easy to implement comparing with batch algorithms. Presently online algorithms usually do not provide with the ability to explicitly control the number of support vectors. A modified online algorithm for SVM is proposed, witch has a budget parameter to explicitly control the number of support vectors. The proposed algorithm was applied to construct intelligent model of helicopter. It is shown by simulation that the modified online algorithm can reduce the number of support vectors effectively with similar generalization ability.
Support Vector Machine Online Algorithms Helicopter Simulation Model
Shuzhou Wang
School of Computer Technology and Automation , Tianjin Polytechnic University, Tianjin 300160 , China
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
1188-1191
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）