期刊
ENVIRONMENTAL RESEARCH
卷 148, 期 -, 页码 24-35出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2016.03.005
关键词
Analytic hierarchy process; Cloud model; Fuzziness; Information entropy; Multi-criteria decision-making; Randomness
资金
- National Key Technology Support Program [2013BAB05B01-3]
- National Natural Science Foundation of China [41571017, 51190091, 41071018]
- Program for New Century Excellent Talents in University [NCET-12-0262]
- China Doctoral Program of Higher Education [20120091110026]
- Qing Lan Project
- Nanjing University
Water quality assessment entails essentially a multi-criteria decision-making process accounting for qualitative and quantitative uncertainties and their transformation. Considering uncertainties of randomness and fuzziness in water quality evaluation, a cloud model-based assessment approach is proposed. The cognitive cloud model, derived from information science, can realize the transformation between qualitative concept and quantitative data, based on probability and statistics and fuzzy set theory. When applying the cloud model to practical assessment, three technical issues are considered before the development of a complete cloud model-based approach: (1) bilateral boundary formula with nonlinear boundary regression for parameter estimation, (2) hybrid entropy-analytic hierarchy process technique for calculation of weights, and (3) mean of repeated simulations for determining the degree of final certainty. The cloud model-based approach is tested by evaluating the eutrophication status of 12 typical lakes and reservoirs in China and comparing with other four methods, which are Scoring Index method, Variable Fuzzy Sets method, Hybrid Fuzzy and Optimal model, and Neural Networks method. The proposed approach yields information concerning membership for each water quality status which leads to the final status. The approach is found to be representative of other alternative methods and accurate. (C) 2016 Elsevier Inc. All rights reserved.
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