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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Main Authors: Shiguo Xu, Tianxiang Wang, Suduan Hu
Format: Article
Language:English
Published: MDPI AG 2015-02-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:http://www.mdpi.com/1660-4601/12/2/2230
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spelling 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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