Application of Grey Clustering Method Based on Improved Analytic Hierarchy Process in Water Quality Evaluation

Wang, Jia; Wang, Xu; Zhang, Xinhua; Li, Haichen; Lei, Xiaohui; Wang, Hao; Wang, Lixin

doi:10.1051/matecconf/201824602004

Cited by 12 publications

(19 citation statements)

References 1 publication

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“…In this case, Shannon Entropy could have been applied alternatively, as was done in the present study, to calculate these weights in an objective and precise way. Similarly, in the study carried out by Wang et al [12] the clustering weights could be obtained through the Shannon Entropy method and be complemented by the Single Factor method used in this study.…”

Section: A Results On the Case Studymentioning

confidence: 99%

Assessment of Surface Water Quality on the Upper Watershed of Huallaga River, in Peru, using Grey Systems and Shannon Entropy

Delgado¹,

Vidal²,

Castro³

et al. 2020

IJACSA

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The assessment of the quality of surface water is a complex issue that entails the comprehensive analysis of several parameters that are altered by natural or man-made causes. In this sense, the Grey Clustering method, which is based on Grey Systems theory, and Shannon Entropy, based on the artificial intelligence approach, provide an alternative to evaluate water quality in an integral way considering the uncertainty within the analysis. In the present study, the water quality on the upper watershed of Huallaga river was evaluated taking into account the monitoring results of twenty-one points carried out by the National Water Authority (ANA) analyzing nine parameters of the Prati index. The results showed that all the monitoring points of the Huallaga river were classified as not contaminated, which means that the discharges, generated by economic activities, are carried out through of treatment plants meeting the quality parameters. Finally, the results obtained can be of great help to the ANA and the regional and local authorities of Peru in making decisions to improve the management of the Huallaga river watershed.

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Section: A Results On the Case Studymentioning

confidence: 99%

Assessment of Surface Water Quality on the Upper Watershed of Huallaga River, in Peru, using Grey Systems and Shannon Entropy

Delgado¹,

Vidal²,

Castro³

et al. 2020

IJACSA

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show abstract

“…In addition, in the assessment of water bodies in the Rimac River [9], they mention that the monitoring points belong to Category 1 A2-Population and Recreation using the Grey Clustering method, so the methodology is similar to the Peruvian RCTs [4], Therefore, in our study, when the results of the application of the Grey Clustering and the results of the participatory monitoring in the 12 monitoring points were compared, in fact it was evident that they complied with the RCT on water [4] in 11 of the points, and in P6 they did not comply with national standards, thus inferring that the results obtained were much more reliable. Finally, this method was used because according to the study conducted on the water quality of the Qingshui River in the city of Duyun, China [10], and compared to the results produced by other methods, it turns out to be more scientific and reasonable and can provide a basis for the evaluation of water quality and the management of the water environment in any space where it is carried out.…”

Section: A About the Methodologymentioning

confidence: 99%

“…In the research paper entitled "Application of Grey Clustering Method Based on Improved Analytic Hierarchy Process in Water Quality Evaluation", they proposed a Grey Clustering method based on an improved analytical hierarchy process to evaluate the water quality of the Qingshui River in Duyun City, by sampling three water periods (periods of abundant, normal and deficient flow) in 4 sections of the river. It was concluded that the water quality of the river belongs to the superclass III according to its regulations, and according to this the contamination is not serious [10].…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of Water Quality in the Lower Huallaga River Watershed using the Grey Clustering Analysis Method

Delgado¹,

Cuadra²,

Simon³

et al. 2021

IJACSA

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Currently, the evaluation of water quality is a topic of global interest, due to its socio-cultural, environmental and economic importance, but in recent years this quality is deteriorating due to inadequate management in the conservation, disposal and use of water by the competent authorities, privatestate entities and the population itself. An alternative to determine the quality of a water body in an integrated manner is the Grey Clustering Method, which was used in this study taking as an indicator the Prati Quality Index, with the objective of making an objective analysis of the quality of the water bodies under study. The case study is the Lower Watershed of the Huallaga River, located between the region of Loreto and San Martin, along which 12 monitoring stations were established to evaluate its surface water quality, through the analysis of 7 parameters: pH, BOD, COD, Total Suspended Solids (TSS), Ammonia Nitrogen, Substrates and Nitrates. Finally, it was determined that the water quality of eleven monitoring stations in the Lower Huallaga River Watershed are within the "Uncontaminated" category, while one monitoring station is within the "Highly Contaminated" category of the Prati Index, this due to its proximity to a landfill. The results obtained in this study, could be useful for the authorities responsible for the protection and sustainable conservation of the Huallaga River Watershed, in order to propose appropriate measures to improve its quality, additionally, this study could be a reference for future studies since the proposed method allowed to prioritize the quality level of the water bodies and identify critical areas.

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“…In addition, the focus of this method is located within the artificial intelligence that is related to the study of problems with little or limited sample information [9]. Which is the reason why the Grey Clustering method has a wide range of applicability such as problem optimization [10], social impact assessment [11], investment risk decision [12] and water quality studies [13]. Furthermore, it is very important to emphasize that traditional methods cannot develop a complex non-linear equation between standard parameters and water quality grades, since there are many factors that modify water quality.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Santa’s river water pollution caused by the environmental liability of Ticapampa using grey clustering method

2020

IJATCSE

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In Peru, many environmental liabilities produce Acid Mine Drainage (AMD) which flow into rivers affecting their water quality, likewise, many of these liabilities transport large amounts of heavy metals, endangering every water-dependent living organism. In this context, for the evaluation of the parameters involved, we used the grey clustering method, which, based on the theory of grey systems, is presented as a remarkable alternative to the classical statistical methods. In this study we assessed the impact of the Ticapampa environmental liability on the water quality of Santa river using data collected in 2010 from four strategically located monitoring points along the river. The analyzed parameters were evaluated according to the parameters established by DS N° 004-2017-MINAM. Results showed that water quality from monitoring points located upstream (P1) and downstream (P2) with respect to the location of the environmental liability and according to Peruvian law, were of A1 (good) quality; which means that it can be purified using disinfectants. On the other hand, at two points located within the limit of the liability, the water quality was identified as A2 (moderate) and A3 (low) quality, which means it can be purified using conventional and special treatment respectively. Therefore, the grey clustering method has proven to be of great utility for water-quality-assessment related studies and can be applied in other studies which focus on this kind of analysis. In addition, the present results can be useful for Peruvian authorities in their decision making benefiting the communities nearby, animals and environment of study.

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Application of Grey Clustering Method Based on Improved Analytic Hierarchy Process in Water Quality Evaluation

Cited by 12 publications

References 1 publication

Assessment of Surface Water Quality on the Upper Watershed of Huallaga River, in Peru, using Grey Systems and Shannon Entropy

Assessment of Surface Water Quality on the Upper Watershed of Huallaga River, in Peru, using Grey Systems and Shannon Entropy

Evaluation of Water Quality in the Lower Huallaga River Watershed using the Grey Clustering Analysis Method

Analysis of Santa’s river water pollution caused by the environmental liability of Ticapampa using grey clustering method

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