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作者:

Sun, Jian (Sun, Jian.) | Meng, Xi (Meng, Xi.) | Qiao, Junfei (Qiao, Junfei.) (学者:乔俊飞)

收录:

EI Scopus SCIE

摘要:

The accurate and real-time measurement of oxygen content in flue gas is the cornerstone of high incineration efficiency and economic benefits for municipal solid waste incineration (MSWI) plants. However, conventional hardware oxygen analyzers are difficult to obtain the oxygen content in flue gas timely and precisely. In this article, a weighted principal component analysis (WPCA) algorithm combined with improved long short-term memory (ILSTM) network is proposed for oxygen content prediction. First, to reduce the model complexity, a WPCA is developed to calculate mutual information correlation coefficients between principal components and the quality variable. Second, the LSTM network is exploited to establish a prediction model, and its hyperparameters are obtained with the particle swarm optimization (PSO) algorithm to improve the generalization ability of the prediction model. Finally, the effectiveness of the proposed prediction method is validated by a benchmark simulation and the real industrial data. And the comparison results with other methodologies demonstrate the considerable prediction performance of the proposed WPCA-ILSTM model.

关键词:

mutual information (MI) municipal solid waste incineration (MSWI) oxygen content prediction principal component analysis (PCA) Long short-term memory (LSTM) network particle swarm optimization (PSO)

作者机构:

  • [ 1 ] [Sun, Jian]Beijing Univ Technol, Fac Informat Technol, Minist Educ, Engn Res Ctr Intelligent Percept & Autonomous Con, Beijing 100124, Peoples R China
  • [ 2 ] [Meng, Xi]Beijing Univ Technol, Fac Informat Technol, Minist Educ, Engn Res Ctr Intelligent Percept & Autonomous Con, Beijing 100124, Peoples R China
  • [ 3 ] [Qiao, Junfei]Beijing Univ Technol, Fac Informat Technol, Minist Educ, Engn Res Ctr Intelligent Percept & Autonomous Con, Beijing 100124, Peoples R China
  • [ 4 ] [Sun, Jian]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China
  • [ 5 ] [Meng, Xi]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China
  • [ 6 ] [Qiao, Junfei]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China

通讯作者信息:

  • 乔俊飞

    [Qiao, Junfei]Beijing Univ Technol, Fac Informat Technol, Minist Educ, Engn Res Ctr Intelligent Percept & Autonomous Con, Beijing 100124, Peoples R China;;[Qiao, Junfei]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China

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来源 :

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

ISSN: 0018-9456

年份: 2021

卷: 70

5 . 6 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:87

JCR分区:1

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 39

ESI高被引论文在榜: 0 展开所有

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中文被引频次:

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