可再生能源2017，Vol.35Issue(8)：1107-1114,8.
垃圾焚烧烟气中二噁英类浓度的支持向量回归预测
Prediction of dioxin emissions in flue gas from waste incineration based on support vector regression
摘要
Abstract
It is difficult to monitor dioxin emissions in flue gas from waste incineration in real time because of the high cost. However, multiple regressions can be applied to predicting dioxin emissions in flue gas, with the aid of pollutant concentrations and operating parameters, which are collected by on-line monitoring systems. The critical problem is that there are very few samples of dioxin available for training prediction models due to the high cost. This leads to a poor performance of generalization when using linear regression models. A nonlinear method named support vector regression is presented in this paper, in order to improve the generalization performance of prediction. This paper compares support vector regression models using three different kernel functions with the multiple linear regression model. Relative errors are calculated to evaluate the generalization performance with the aid of 10 sets of data monitored on a waste incineration plant in South China. The result shows support vector regression models have lower relative errors. The maximum possible percentage errors of models using first-order polynomial kernel function and radial basis kernel function are much lower than the model using Sigmoid kernel function, especially.关键词
垃圾焚烧/烟气/二噁英类/小样本/支持向量回归Key words
waste incineration/flue gas/dioxin/small sample/support vector regression分类
能源科技引用本文复制引用
肖晓东,卢加伟,海景,廖利..垃圾焚烧烟气中二噁英类浓度的支持向量回归预测[J].可再生能源,2017,35(8):1107-1114,8.基金项目
国家自然科学基金项目(51608223) （51608223）
中央级公益性科研院所基本科研业务专项(PM-zx703-201602-050). （PM-zx703-201602-050）
