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Water Quality Assessment using Association Rule Mining for River Narmada
Objective: The objective of the this study is to analyze the various water quality parameters of the Narmada River and to find hidden relationship between them so that it suggest some decision plans or policies to predict or classify the water quality. Methods: In this study we find an approach to water quality management through Association or correlation studies between various water quality parameters. The Data Mining Technique called Association Rule Mining (Apriori Algorithm) is used to find and extract some rules or relationship between various water quality parameters for Narmada River at Harda and Hoshangabad districts of Madhy Pradesh. Findings: We have found some interesting and useful correlation between different water quality parameters and also we measure the performance of algorithm by the confidence and lift value factors. Application: This research present a model with actual data both for spatial and temporal patters and benefits of employing data mining techniques towards the improvement of water quality management plans. These results conclude that there is urgent need of strict regulatory monitoring for water quality maintenance in the river system at Hoshangabad District.
Keywords
Apriori Algorithm, Association Rule Mining
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