基于PSO-SVR的下水道可燃气体分析

Wang Hong-qi, Cheng Xin-wen, Jiang Hua-long
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引用次数: 0

摘要

针对下水道可燃气体的非线性、选择性和交叉灵敏度较差的特点,建立了基于PSO-SVR机的下水道可燃气体分析预测模型,该模型引入了新的粒子群算法来支持向量回归机对重要参数进行优化,实现了SVR机参数的自动确定。并用于下水道可燃气体的定量分析。仿真结果表明,基于PSO-SVR机的下水道可燃气体模型优于与之比较的SVR模型,具有更好的泛化性能和更高的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Analysis of Sewers Inflammable Gas Based on PSO-SVR
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.
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