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Author:

Tang, Jian (Tang, Jian.) (Scholars:汤健) | Qiao, Jun-Fei (Qiao, Jun-Fei.) (Scholars:乔俊飞) | Xu, Zhe (Xu, Zhe.) | Guo, Zi-Hao (Guo, Zi-Hao.)

Indexed by:

EI Scopus CSCD

Abstract:

Municipal solid waste incineration (MSWI) process produces a type of highly toxic and persistent pollutant, i.e., Dioxins (DXN), which has tremendous realistic and potential hazards to the ecological environment and human health. It is very important for optimizing operation of MSWI process and controlling urban pollution in terms of realization of continuous real-time measurement of DXN emission concentration. The generation mechanism of DXN is very complex. Thus, there is a complex non-linear mapping relationship between DXN and input/output variables of MSWI process. Aim at these problems, a soft measuring method of DXN emission concentration based on feature selection and selective ensemble strategy is proposed. Firstly, the process variables of easy-to-measure are matched to obtain the modeling sample with characteristics of small sample and high dimension. Then, the variable projection importance (VIP) value based on linear projection to latent structure algorithm and input feature selection ratio based on expert experience are used to select the input features. At last, by using ensemble construction strategy based on manipulating training sample with characteristic of adaptive select kernel parameter is constructed. The proposed method is simulated and validated by using the data of DXN emission concentration in reference and actual MSWI process. © 2021, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.

Keyword:

Municipal solid waste Air pollution Feature extraction Waste incineration Organic pollutants Health hazards

Author Community:

  • [ 1 ] [Tang, Jian]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Tang, Jian]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 3 ] [Qiao, Jun-Fei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Qiao, Jun-Fei]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China
  • [ 5 ] [Xu, Zhe]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Guo, Zi-Hao]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Guo, Zi-Hao]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing; 100124, China

Reprint Author's Address:

  • 汤健

    [tang, jian]beijing key laboratory of computational intelligence and intelligent system, beijing; 100124, china;;[tang, jian]faculty of information technology, beijing university of technology, beijing; 100124, china

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Source :

Control Theory and Applications

ISSN: 1000-8152

Year: 2021

Issue: 1

Volume: 38

Page: 110-120

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 20

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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