Prediction Model of Dioxin Emission Concentration in MSW Incineration Process Based on Stochastic Configuration Network

Abstract

The increasing municipal solid waste has become one of the stubborn diseases of modern society. Incineration technology with the advantage of reduction and resource utilization is an important avenue to solve this problem. Toxic gases emitted from incineration not only pollute the environment but also pose a serious threat to human health. However, the complexity of incineration process brings great difficulty to the detection of pollutants concentration in the exhaust gases. In order to address the problem that the concentration of pollutants is difficult to predict, a prediction model of dioxin emission concentration based on stochastic configuration network is developed in this paper. The prediction model takes the online operation data of municipal solid waste incineration power plant as input parameters and realizes the online prediction of dioxin emission concentration. It provides a scientific basis for choosing the appropriate control strategy. When compared with BP neural network, RBF neural network and support vector machine prediction model, it is easily found that the proposed prediction model can effectively improve the prediction accuracy of dioxin emission concentration during the municipal solid waste incineration process.