Prediction of Dioxin Emission Concentration from Municipal Solid Waste Incineration Process Based on PSO and Equispaced Interpolation

As currently widely used municipal solid waste resource treatment method, the municipal solid waste incineration (MSWI) process emit dioxins (DXN) compound s with high toxicity and persistent pollution characteristics. It is one of the main reasons that cause incineration power plants to have a "Not in my back yard". At present, the long-period, high-cost offline detection method used in industrial sites cannot achieve real-time monitoring of DXN emission concentration. Moreover, the number of samples used to build a DXN emission concent ration prediction model is extremely scarce. Aim at the above problems, a method for predicting DXN emission concentration in MSWI process based on PSO and equi spaced interpolation is proposed. At first, the domain of original small sample input and output is expanded based on the improved mega-trend-diffusion(MTD) technology. Then, the equal interval interpolation method is used to generate the virtual sample inputs, which are used to obtain the virtual sample output s by combining the mapping model. The above results are combined with the expansion space to delete the bad virtual samples. Thirdly, the PSO algorithm is used to optimize and select the reduced virtual sample set. Finally, a mixed sample set composed of the optimized selected virtual sample set and the original small sample set is used to construct a DXN emission concentration prediction model. The effectiveness of the proposed method is verified with the actual detection data of DXN for many years in a MSWI plant.