LAPSE:2019.0512
Published Article
LAPSE:2019.0512
Integration Multi-Model to Evaluate the Impact of Surface Water Quality on City Sustainability: A Case from Maanshan City in China
Zhanbo Chen, Hui Zhang, Mingxia Liao
April 15, 2019
Water pollution is a worldwide problem that needs to be solved urgently and has a significant impact on the efficiency of sustainable cities. The evaluation of water pollution is a Multiple Criteria Decision-Making (MCDM) problem and using a MCDM model can help control water pollution and protect human health. However, different evaluation methods may obtain different results. How to effectively coordinate them to obtain a consensus result is the main aim of this work. The purpose of this article is to develop an ensemble learning evaluation method based on the concept of water quality to help policy-makers better evaluate surface water quality. A valid application is conducted to illustrate the use of the model for the surface water quality evaluation problem, thus demonstrating the effectiveness and feasibility of the proposed model.
Keywords
ensemble learning, MCDM, multi-model evaluation, water pollution
Suggested Citation
Chen Z, Zhang H, Liao M. Integration Multi-Model to Evaluate the Impact of Surface Water Quality on City Sustainability: A Case from Maanshan City in China. (2019). LAPSE:2019.0512
Author Affiliations
Chen Z: School of Information and Statistics, Guangxi University of Finance and Economics, Nanning 530003, China
Zhang H: School of Information and Statistics, Guangxi University of Finance and Economics, Nanning 530003, China
Liao M: School of Information and Statistics, Guangxi University of Finance and Economics, Nanning 530003, China
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Journal Name
Processes
Volume
7
Issue
1
Article Number
E25
Year
2019
Publication Date
2019-01-08
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr7010025, Publication Type: Journal Article
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LAPSE:2019.0512
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doi:10.3390/pr7010025
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Apr 15, 2019
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CC BY 4.0
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[v1] (Original Submission)
Apr 15, 2019
 
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Apr 15, 2019
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Original Submitter
Calvin Tsay
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