Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model
Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed...
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doaj-5997b6de894f43b9b69a5c948b22f60f2020-11-24T23:08:32ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012015-02-011222230224810.3390/ijerph120202230ijerph120202230Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition ModelShiguo Xu0Tianxiang Wang1Suduan Hu2Faculty of Infrastructure Engineering, School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, ChinaFaculty of Infrastructure Engineering, School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, ChinaFaculty of Infrastructure Engineering, School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, ChinaWater quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results.http://www.mdpi.com/1660-4601/12/2/2230water quality assessmentfuzzificationdynamicinterval influencecharacteristic level value |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shiguo Xu Tianxiang Wang Suduan Hu |
spellingShingle |
Shiguo Xu Tianxiang Wang Suduan Hu Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model International Journal of Environmental Research and Public Health water quality assessment fuzzification dynamic interval influence characteristic level value |
author_facet |
Shiguo Xu Tianxiang Wang Suduan Hu |
author_sort |
Shiguo Xu |
title |
Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model |
title_short |
Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model |
title_full |
Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model |
title_fullStr |
Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model |
title_full_unstemmed |
Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model |
title_sort |
dynamic assessment of water quality based on a variable fuzzy pattern recognition model |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1660-4601 |
publishDate |
2015-02-01 |
description |
Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results. |
topic |
water quality assessment fuzzification dynamic interval influence characteristic level value |
url |
http://www.mdpi.com/1660-4601/12/2/2230 |
work_keys_str_mv |
AT shiguoxu dynamicassessmentofwaterqualitybasedonavariablefuzzypatternrecognitionmodel AT tianxiangwang dynamicassessmentofwaterqualitybasedonavariablefuzzypatternrecognitionmodel AT suduanhu dynamicassessmentofwaterqualitybasedonavariablefuzzypatternrecognitionmodel |
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1725613802843537408 |