The Analysis of Sewers Inflammable Gas Based on PSO-SVR

被引：0
|
作者：
Wang Hong-qi [1 ]
Cheng Xin-wen [1 ]
Jiang Hua-long [1 ]
机构：
[1] Sichuan Univ Sci & Engn, Sch Comp Sci, Zigong 643000, Sichuan, Peoples R China
来源：
2013 THIRD INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC) | 2013年
关键词：
Support Vector Regression; Particle Swarm Optimization (PSO); Inflammable Gas; Prediction model;
D O I：
10.1109/IMCCC.2013.134
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Due to the non-liner, poor selectivity and cross-sensitivity of the combustible gas in the sewer, an analysis prediction model of the combustible gas in the sewer has been established based on the PSO-SVR machine; the model has introduced a new particle swarm algorithm to support the vector regression machine so that it can optimize the important parameters, realizing the automatic determination of parameters of the SVR machine, and be used for quantitative analysis of combustible gas in the sewer. The simulation results show that the model of the combustible gas in the sewer based on PSO-SVR machine is superior to the compared SVR model and it has better generalization performance and higher prediction accuracy.
引用
收藏
页码：598 / 602
页数：5
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