Dioxin emission modeling using feature selection and simplified DFR with residual error fitting for the grate-based MSWI process
Copyright © 2023 Elsevier Ltd. All rights reserved.
| Veröffentlicht in: | Waste management (New York, N.Y.). - 1999. - 168(2023) vom: 01. Aug., Seite 256-271 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | Waste management (New York, N.Y.) |
| Schlagworte: | Journal Article Deep forest regression (DFR) Dioxin emission Municipal solid waste incineration (MSWI) Residual error fitting Soft-sensor measurement Solid Waste Dioxins Polychlorinated Dibenzodioxins |
| Zusammenfassung: | Copyright © 2023 Elsevier Ltd. All rights reserved. Municipal solid waste incineration (MSWI) with grate technology is a widely applied waste-to-energy process in various cities in China. Meanwhile, dioxins (DXN) are emitted at the stack and are the critical environmental indicator for operation optimization control in the MSWI process. However, constructing a high-precision and fast emission model for DXN emission operation optimization control becomes an immediate difficulty. To address the above problem, this research utilizes a novel DXN emission measurement method using simplified deep forest regression (DFR) with residual error fitting (SDFR-ref). First, the high-dimensional process variables are optimally reduced following the mutual information and significance test. Then, a simplified DFR algorithm is established to infer or predict the nonlinearity between the selected process variables and the DXN emission concentration. Moreover, a gradient enhancement strategy in terms of residual error fitting with a step factor is designed to improve the measurement performance in the layer-by-layer learning process. Finally, an actual DXN dataset from 2009 to 2020 of the MSWI plant in Beijing is utilized to verify the SDFR-ref method. Comparison experiments demonstrate the superiority of the proposed method over other methods in terms of measurement accuracy and time consumption |
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| Beschreibung: | Date Completed 22.08.2023 Date Revised 22.08.2023 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1879-2456 |
| DOI: | 10.1016/j.wasman.2023.05.056 |