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Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model

Author

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  • Shiguo Xu

    (Faculty of Infrastructure Engineering, School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China)

  • Tianxiang Wang

    (Faculty of Infrastructure Engineering, School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China)

  • Suduan Hu

    (Faculty of Infrastructure Engineering, School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China)

Abstract

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.

Suggested Citation

  • Shiguo Xu & Tianxiang Wang & Suduan Hu, 2015. "Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model," IJERPH, MDPI, vol. 12(2), pages 1-19, February.
    • Handle: RePEc:gam:jijerp:v:12:y:2015:i:2:p:2230-2248:d:45944
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    References listed on IDEAS

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    1. Wen-chuan Wang & Dong-mei Xu & Kwok-wing Chau & Guan-jun Lei, 2014. "Assessment of River Water Quality Based on Theory of Variable Fuzzy Sets and Fuzzy Binary Comparison Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4183-4200, September.
    2. Yuankun Wang & Dong Sheng & Dong Wang & Huiqun Ma & Jichun Wu & Feng Xu, 2014. "Variable Fuzzy Set Theory to Assess Water Quality of the Meiliang Bay in Taihu Lake Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 867-880, February.
    3. Yan An & Zhihong Zou & Ranran Li, 2014. "Water Quality Assessment in the Harbin Reach of the Songhuajiang River (China) Based on a Fuzzy Rough Set and an Attribute Recognition Theoretical Model," IJERPH, MDPI, vol. 11(4), pages 1-14, March.
    4. Fereshteh Modaresi & Shahab Araghinejad, 2014. "A Comparative Assessment of Support Vector Machines, Probabilistic Neural Networks, and K-Nearest Neighbor Algorithms for Water Quality Classification," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4095-4111, September.
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    Cited by:

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    3. Zeyu Wang & Juqin Shen & Fuhua Sun & Zhaofang Zhang & Dandan Zhang & Yizhen Jia & Kaize Zhang, 2019. "A Pricing Model for Groundwater Rights in Ningxia, China Based on the Fuzzy Mathematical Model," IJERPH, MDPI, vol. 16(12), pages 1-20, June.
    4. Suduan Hu & Tianxiang Wang & Shiguo Xu & Lingxiao Ma & and Xinguo Sun, 2019. "Seasonal Release Potential of Sediments in Reservoirs and its Impact on Water Quality Assessment," IJERPH, MDPI, vol. 16(18), pages 1-17, September.

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