An Intelligent Groundwater Management Recommender System

A A Abd El Aziz; Khalaf Okab Alsalem; Mahmood A Mahmood

doi:10.17485/IJST/v14i37.1332

Article

An Intelligent Groundwater Management Recommender System

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v14i37.1332

Year: 2021, Volume: 14, Issue: 37, Pages: 2871-2879

Original Article

An Intelligent Groundwater Management Recommender System

A A Abd El-Aziz¹,^2*, Khalaf Okab Alsalem¹, Mahmood A Mahmood¹,²

¹Department of Information Systems, College of Computer and Information Sciences, Jouf University, KSA
²Department of Information Systems & Technology, FGSSR, Cairo University, Egypt

*Corresponding Author
Email: [email protected]

Received Date:18 July 2021, Accepted Date:21 October 2021, Published Date:09 November 2021

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

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%.

Keywords: Groundwater Management; Intelligent System; Recommender Systems; Datamining; Machine Learning; Deep Learning

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Copyright

© 2021 A A Abd El-Aziz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)