期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：11
DOI：10.14569/IJACSA.2020.0111156
出版社：Science and Information Society (SAI)
摘要：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.
关键词：Grey clustering; Huallaga river; Prati index; Shannon entropy; water quality
