Author(s): Annie Jose; Srinivas Yasala
Linked Author(s):
Keywords: Groundwater Quality; Machine learning; Meta-model stacking; Kanyakumari District; Prediction
Abstract: Groundwater quality is a crucial resource for human activities, but rising pollution levels are causing concerns about its quality. Preserving groundwater quality is challenging but Machine learning algorithms can be beneficial for managing and predicting groundwater quality using large datasets. This research uses including 10-years of groundwater quality and rainfall datasets from the Kanyakumari District, Tamil Nadu, India on Machine learning method called meta model stacking which incorporates the stacking of the base learners – k Nearest Neighbors, Support Vector Machine, Logistic Regression and the overall prediction is done by the meta-learner, Artificial Neural Network (ANN) to improve overall accuracy. The proposed stacking model achieved a 97% accuracy, demonstrating its potential as a reliable tool for managing water resources and establishing policies in complex environmental challenges. This also helps in enhancing the sustainable use of groundwater resources in the Kanyakumari District, Tamil Nadu, India.
Year: 2024