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dc.contributor.authorJitha P, Nair-
dc.contributor.authorVijaya, M S-
dc.date.accessioned2023-11-03T06:43:48Z-
dc.date.available2023-11-03T06:43:48Z-
dc.date.issued2022-
dc.identifier.urihttps://iopscience.iop.org/article/10.1088/1742-6596/2325/1/012011/pdf-
dc.description.abstractVarious pollutants have had a substantial impact on the quality of water in recent years. The quality of water directly impacts human health and the environment. The water quality index (WQI) is an indicator of effective water management. Water quality modelling and prediction have become essential in the fight against water pollution. The research aims to build an efficient prediction model for river water quality and to categorize the index value according to the water quality standards. The data has been collected from eleven sampling stations located in various locations across the Bhavani River, which flows through Kerala and Tamilnadu. The water quality index is determined by 27different parameters affecting water quality like dissolved oxygen, temperature, pH, alkalinity, hardness, chloride, coliform, etc. Data normalization and feature selection are done to construct the dataset to develop machine learning models. Machine learning algorithms such as linear regression, MLP regressor, support vector regressor and random forest has been employed to build a water quality prediction model. Support vector machines (SVM), naïve bayes, decision trees, MLP classifiers, have been used to develop a classification model for classifying water quality index. The experimental results revealed that the MLP regressor efficiently predicts the water Quality index with root mean squared error as 2.432, MLP classifier classifies the water quality index with 81% accuracy. The developed models show promising output concerning water quality index prediction and classification.en_US
dc.language.isoen_USen_US
dc.publisherIOP Publishing Ltden_US
dc.subjectRiver water qualityen_US
dc.subjectPrediction modelen_US
dc.subjectClassification modelen_US
dc.subjectExploratory data analysisen_US
dc.subjectMachine learning algorithms.en_US
dc.titleRIVER WATER QUALITY PREDICTION AND INDEX CLASSIFICATION USING MACHINE LEARNINGen_US
dc.typeOtheren_US
Appears in Collections:4.Conference Paper (11)

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