Applications of Gaussian process regression for predicting blue water footprint: Case study in Ad Daqahliyah, Egypt-Reference-Cited by-同舟云学术

Applications of Gaussian process regression for predicting blue water footprint: Case study in Ad Daqahliyah, Egypt

Published:2021-09 Issue: Volume:255 Page:107052
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

Elbeltagi Ahmed,Azad Nasrin,Arshad Arfan,Mohammed Safwan,Mokhtar Ali,Pande Chaitanya,Etedali Hadi Ramezani,Bhat Shakeel Ahmad,Islam Abu Reza Md. Towfiqul,Deng Jinsong

Funder

Ministry of Science and Technology of the People's Republic of China

Natural Science Foundation of Zhejiang Province

Zhejiang University

Publisher

Elsevier BV

Subject

Earth-Surface Processes,Soil Science,Water Science and Technology,Agronomy and Crop Science

Reference79 articles.

1. Water footprint assessment of main cereals in Iran;Ababaei;Agric. Water Manag.,2017

2. Evaluation of CSM-Ceres-Maize Model for simulating maize production in Northern Delta of Egypt;Abdrabbo;Life Sci.,2013

3. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015;Abatzoglou;Sci. Data,2018

4. Novel ensemble forecasting of streamflow using locally weighted learning algorithm;Adnan;Sustainability,2021

5. Evaluation of the effect of climate change on maize water footprint under RCPs scenarios in Qazvin plain, Iran;Ahmadi;Agric. Water Manag.,2021

Cited by 43 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Re-vitalizing wastewater: Nutrient recovery and carbon capture through microbe-algae synergy using omics-biology;Environmental Research;2024-10

2. Water Supply Forecasting Model in the Chi River from Satellite Images;2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE);2024-06-19

3. Interpretable machine learning of SPAC system via a mechanism-assisted gaussian process group: Representation of the system mechanism by data;Computers and Electronics in Agriculture;2024-06

4. Evaluation of water quality based on artificial intelligence: performance of multilayer perceptron neural networks and multiple linear regression versus water quality indexes;Environment, Development and Sustainability;2024-06-01

5. Tailoring thin film composite membranes for clean water production: A study on structural variations and predictive insights using machine learning;Journal of Environmental Chemical Engineering;2024-06