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Quality Assessment of Ground Water on Small Dataset

Publication Type : Journal Article

Publisher : International Journal of Innovative Technology and Exploring Engineering (IJITEE)

Source : International Journal of Innovative Technology and Exploring Engineering (IJITEE), Volume 8, Issue 5 (2019)

Url : https://www.ijitee.org/wp-content/uploads/papers/v8i5/E3134038519.pdf

Campus : Kochi

School : School of Arts and Sciences

Department : Computer Science

Year : 2019

Abstract : Quality assessment of water has a lot of attractions during recent years. Diverse kinds of classification and monitoring techniques were used in this field of study. The present examination investigates the quality of ground water in Kudankulam which is situated Tirunelveli district of Tamil Nadu. A total of 19 samples was accumulated in this region typically from the coastal area during 2011-2012.The evaluation was done on the basis chemical parameters of each samples. This paper explores various classifier models such as KNN, NB and SVM to achieve prediction of groundwater quality. The classification is done based on the Water Quality Index (WQI) of each sample. A near investigation of characterization systems was done dependent on the confusion matrix, accuracy, f1 score, precision and recall. The outcomes propose that SVM is a better method having high accuracy rate than other models.

Cite this Research Publication : Aiswarya Vijayakumar and A. S. Mahesh, “Quality Assessment of Ground Water on Small Dataset”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), vol. 8, no. 5, 2019.

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