The Analysis of Sewers Inflammable Gas Based on PSO-SVR

Author

Wang Hong-qi ; Cheng Xin-Wen ; Jiang Hua-Long

Author_Institution

Sch. of Comput. Sci., Sichuan Univ. of Sci. & Eng., Zigong, China

fYear

2013

fDate

21-23 Sept. 2013

Firstpage

598

Lastpage

602

Abstract

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.

Keywords

gas sensors; particle swarm optimisation; regression analysis; support vector machines; PSO-SVR machine; combustible gas; gas detection; particle swarm optimisation; prediction model; sewers inflammable gas analysis; support vector regression; Accuracy; Analytical models; Data models; Educational institutions; Particle swarm optimization; Predictive models; Support vector machines; Inflammable Gas; Particle Swarm Optimization (PSO); Prediction model; Support Vector Regression;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on

Conference_Location

Shenyang

Type

conf

DOI

10.1109/IMCCC.2013.134

Filename

6840524