Publication Type : Journal Article
Source : International Journal of Recent Technology and Engineering (IJRTE) , Volume 8, Issue 2 (2019)
Url : https://www.ijrte.org/wp-content/uploads/papers/v8i2/B3709078219.pdf
Campus : Kochi
School : School of Arts and Sciences
Department : Computer Science
Year : 2019
Abstract : Quality assessment of water is one of the basic points which have pulled in a lot of thought in the progressing years. Diverse kinds of classification system are most convenient for the examination in this field of study. The present examination investigates the quality of ground water in Agastheeswaram which is located in Tamilnadu. Totally 138 water samples was accumulated in the midst of pre-monsoon (PRM) and post-monsoon (PSM) from the year of 2011 to 2012.The water quality (WQ) evaluation was carried out by assessing chemical parameters for both the seasons. This paper explores various classifier models such as DT, KNN and SVM to achieve prediction of groundwater quality. The classification is done based on the 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 in Pre and Post-Monsoon Using Various Classification Technique”, International Journal of Recent Technology and Engineering (IJRTE) , vol. 8, no. 2, 2019.