Influence of exogenous factors on water demand forecasting models during the COVID-19 period-Reference-Cited by-同舟云学术

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Influence of exogenous factors on water demand forecasting models during the COVID-19 period

Published:2023-01 Issue: Volume:117 Page:105617
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Abu Talib Manar^ORCID,Abdallah Mohamed^ORCID,Abdeljaber Abdulrahman^ORCID,Abu Waraga Omnia

Funder

University of Sharjah

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference61 articles.

1. Artificial intelligence applications in solid waste management: A systematic research review;Abdallah;Waste Manage.,2020

2. Forecasting highly fluctuating electricity load using machine learning models based on multimillion observations;Abdallah;Adv. Eng. Inform.,2022

3. Quantifying the impact of the COVID-19 lockdown on household water consumption patterns in England;Abu-Bakar;NPJ Clean Water,2021

4. Boosted ANFIS model using augmented marine predator algorithm with mutation operators for wind power forecasting;Al-qaness;Appl. Energy,2022

5. Modified aquila optimizer for forecasting oil production;Al-qaness;Geo-Spat. Inf. Sci.,2022

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1. Comparative Analysis of Machine Learning Techniques for Water Consumption Prediction: A Case Study from Kocaeli Province;Sensors;2024-09-09

2. Drought prediction using artificial intelligence models based on climate data and soil moisture;Scientific Reports;2024-08-24

3. Interpretable knowledge-guided framework for modeling reservoir water-sensitivity damage based on Light Gradient Boosting Machine using Bayesian optimization and hybrid feature mining;Engineering Applications of Artificial Intelligence;2024-07

4. A Demographic Vulnerability of Pandemic Prediction: Deep Learning for Effective Social Distancing Beyond Lockdowns;2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC);2023-11-14

5. Spatial-Temporal Correlation Neural Network for Long Short-Term Demand Forecasting During COVID-19;IEEE Access;2023

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