华东交通大学学报Issue(1)：121-127,7.
PSO-SVM算法在智能建筑环境监控系统中的应用
Application of PSO-SVM Algorithm in Environmental Monitoring System of Intelligent Building
傅军栋 1邹欢 1康水华1
作者信息
- 1. 华东交通大学电气与电子工程学院，江西 南昌 330013
- 折叠
摘要
Abstract
In environmental monitoring system of intelligent buildings, independent work of multiple sensors may cause misjudgment. Aiming at this problem, this paper proposes an environmental quality comprehensive evalua tion model for optimizing the Support Vector Machine (SVM) by using the Particle Swarm Optimization (PSO) al-gorithm, in which the SVM parameters of the punishment and the kernel function are optimized by PSO and the established SVM classifiers are trained and tested by using the sample data collected by ZigBee wireless sensor networks. The experimental results show that the average recognition rate of the PSO-SVM classifier is up to 94.44% in evaluating environmental quality, and the classification results are stable. It suggests that the pro-posed method increase the accuracy of monitoring data and improve working reliability for the environmental monitoring system of intelligent buildings.关键词
环境监控/多传感器/粒子群优化/支持向量机Key words
environmental monitoring/multiple sensor/particle swarm optimization (PSO)/support vector ma-chine(SVM)分类
信息技术与安全科学引用本文复制引用
傅军栋,邹欢,康水华..PSO-SVM算法在智能建筑环境监控系统中的应用[J].华东交通大学学报,2016,(1):121-127,7.
