Prediction of Chemical Gas Emissions Based on Ecological Environment
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-04
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
With the serious pollution of the ecological environment, there are a large number of harmful gases in the chemical gases emitted by the industry.
Relevant intelligent chemical algorithms control the emission of chemical gases, which can effectively reduce emissions and predict emissions more accurately.
This paper proposes a gray wolf optimization algorithm based on chaotic search strategy combined with extreme learning machine to predict chemical emission gases, taking a 330 MW pulverized coal-fired boiler as a test object and establishing chemical emissions of CNGWO-ELM.
The prediction model, by using the relevant data collected by DCS as training samples and test samples, trains and tests the model.
Simulation experiments show that the chemical emission prediction model of CNGWO-ELM has better accuracy and stronger generalization ability, with higher practical value.
American Psychological Association (APA)
Chen, Guobin& Li, Shijin. 2020. Prediction of Chemical Gas Emissions Based on Ecological Environment. Journal of Chemistry،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1182193
Modern Language Association (MLA)
Chen, Guobin& Li, Shijin. Prediction of Chemical Gas Emissions Based on Ecological Environment. Journal of Chemistry No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1182193
American Medical Association (AMA)
Chen, Guobin& Li, Shijin. Prediction of Chemical Gas Emissions Based on Ecological Environment. Journal of Chemistry. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1182193
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1182193