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Water 2017, 9(5), 308; doi:10.3390/w9050308

Expert Decision Support Technique for Algal Bloom Governance in Urban Lakes Based on Text Analysis

1
School of Automation, Beijing Institute of Technology, Beijing 100081, China
2
School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China
*
Author to whom correspondence should be addressed.
Academic Editor: Peter Coombes
Received: 15 February 2017 / Revised: 5 April 2017 / Accepted: 24 April 2017 / Published: 28 April 2017
(This article belongs to the Special Issue Urban Water Challenges)
View Full-Text   |   Download PDF [1020 KB, uploaded 28 April 2017]   |  

Abstract

As a typical phenomenon of eutrophication pollution, algal bloom threatens public health and water security. The governance of algal bloom is largely affected by administrators’ knowledge and experience, which may lead to a subjective and one-sided decision-making result. Meanwhile, experts in the specific field can provide professional support. How to utilize expert resources adequately and automatically has been a problem. This paper proposes an expert decision support technique for algal bloom governance based on text analysis methods. Firstly, the decision support mechanism is introduced to form a general decision-making framework. Secondly, the expert classification method is proposed to help with choosing suitable experts. Thirdly, a multi-criteria group decision-making method is presented based on the automatic analysis of experts’ decision opinions. Finally, an experiment is conducted to verify the expert decision support technique. The results show the technique’s feasibility and rationality. This paper describes experts’ information and opinions with natural language, which can intuitively reflect the natural meaning. The expert decision support technique based on text analysis broadens the management thought of water pollution in urban lakes. View Full-Text
Keywords: algal bloom; eutrophication; urban lake; governance decision-making; text analysis algal bloom; eutrophication; urban lake; governance decision-making; text analysis
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MDPI and ACS Style

Bai, Y.-T.; Zhang, B.-H.; Wang, X.-Y.; Jin, X.-B.; Xu, J.-P.; Wang, Z.-Y. Expert Decision Support Technique for Algal Bloom Governance in Urban Lakes Based on Text Analysis. Water 2017, 9, 308.

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