An Intelligent Groundwater Management Recommender System

Objectives: To explore the area of groundwater that can assist to improve the accessibility of freshwater. Methods : We propose a machine-deep learning model based on a recommender system to manage and classify groundwater. Finding: The main goal of our proposed approach is to classify groundwater into multi-labels, which are drinking water (Excellent or Good) or Irrigation water (Poor or Very Poor) with guarantee a higher accuracy score. The recommender system is applied on the testing dataset and the accuracy of the deep learning technique was 91% and the accuracy of machine leaning technique was 84%.