文章基本信息

标题：Application of SVM Optimization Based on GA in Electronic Sphygmomanometer Data Fusion
本地全文：下载
作者：Fengmei Gao ; Tao Lin
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2013
卷号：10
期号：1
出版社：IJCSI Press
摘要：If the proper kernel function parameter? is chosen, using of the multi-sensor data fusion method based on SVM, the influence of cross sensitive disturbance variables including the temperatureT and the power supply current I , can be significantly suppressed and the stability of the pressure sensor can be improved in the electronic sphygmomanometer. While kernel function parameter? is difficult to ascertain after repeated test. GA(Genetic Algorithm) with powerful global searching for optimal solutions is able to meet the requirement of optimization for kernel function parameter? of SVM(Support Vector Machine).
关键词：SVM; GA; Kernel Function Parameter; Multi;sensor Data Fusion