A Method of Nonlinear Error Calibration Based on Model for GA and SVM
It is an important factor that the measuring accuracy on virtual instrument is influenced by nonlinear errors. Nonlinear errors must be calibrated in use for ensuring virtual instruments specification. A new regression algorithm model for support vector machine based on genetic algorithm (GA) had been put forward in this paper . The genetic algorithm was put into use in the parameters optimization of support vector machine taking advantage of the genetic algorithms merit. The learning capability and generalization capability of SVM would be improved effectively. The validity was validated by an experimentation of building a virtual instrument on DAQ using above mentioned the method. The result indicated the method was feasible and the measure precision was increased evidently.
Virtual Instrument Nonlinear Calibration Support Vector Machines (SVM) Genetic Algorithm
LI Shiping TANGChao
Xian Research Inst. of Hi-Tech Hongqing Town, Xian, P.R. China, 710025
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）