|
[1]
|
Use of meta-heuristic approach in the estimation of aquifer's response to climate change under shared socioeconomic pathways
Groundwater for Sustainable Development,
2023
DOI:10.1016/j.gsd.2022.100882
|
|
|
|
|
[2]
|
Water and wastewater quality prediction: current trends and challenges in the implementation of artificial neural network
Environmental Monitoring and Assessment,
2023
DOI:10.1007/s10661-022-10904-0
|
|
|
|
|
[3]
|
Non-carcinogenic health risk assessment and predicting of pollution indexing of groundwater around Osisioma, Nigeria, using artificial neural networks and multi-linear modeling principles
Stochastic Environmental Research and Risk Assessment,
2023
DOI:10.1007/s00477-023-02398-0
|
|
|
|
|
[4]
|
Water and wastewater quality prediction: current trends and challenges in the implementation of artificial neural network
Environmental Monitoring and Assessment,
2023
DOI:10.1007/s10661-022-10904-0
|
|
|
|
|
[5]
|
Non-carcinogenic health risk assessment and predicting of pollution indexing of groundwater around Osisioma, Nigeria, using artificial neural networks and multi-linear modeling principles
Stochastic Environmental Research and Risk Assessment,
2023
DOI:10.1007/s00477-023-02398-0
|
|
|
|
|
[6]
|
The sources, leaching, remediation, and environmental concerns associated with groundwater salinity
Environmental Science and Pollution Research,
2023
DOI:10.1007/s11356-023-29601-7
|
|
|
|
|
[7]
|
Delineation of groundwater potential zones in KwaZulu-Natal, South Africa using remote sensing, GIS and AHP
Journal of African Earth Sciences,
2022
DOI:10.1016/j.jafrearsci.2022.104571
|
|
|
|
|
[8]
|
Groundwater Level Modeling with Machine Learning: A Systematic Review and Meta-Analysis
Water,
2022
DOI:10.3390/w14060949
|
|
|
|
|
[9]
|
Sustainable Energy-Water-Environment Nexus in Deserts
Advances in Science, Technology & Innovation,
2022
DOI:10.1007/978-3-030-76081-6_1
|
|
|
|
|
[10]
|
Delineation of groundwater potential zones in KwaZulu-Natal, South Africa using remote sensing, GIS and AHP
Journal of African Earth Sciences,
2022
DOI:10.1016/j.jafrearsci.2022.104571
|
|
|
|
|
[11]
|
Computational assessment of groundwater salinity distribution within coastal multi-aquifers of Bangladesh
Scientific Reports,
2022
DOI:10.1038/s41598-022-15104-x
|
|
|
|
|
[12]
|
Groundwater quality forecasting modelling using artificial intelligence: A review
Groundwater for Sustainable Development,
2021
DOI:10.1016/j.gsd.2021.100643
|
|
|
|
|
[13]
|
Soil salinity mapping by remote sensing south of Urmia Lake, Iran
Geoderma Regional,
2020
DOI:10.1016/j.geodrs.2020.e00317
|
|
|
|
|
[14]
|
Investigation of the Influence of Excess Pumping on Groundwater Salinity in the Gaza Coastal Aquifer (Palestine) Using Three Predicted Future Scenarios
Water,
2020
DOI:10.3390/w12082218
|
|
|
|
|
[15]
|
River Water Salinity Prediction Using Hybrid Machine Learning Models
Water,
2020
DOI:10.3390/w12102951
|
|
|
|
|
[16]
|
Groundwater level forecasting using soft computing techniques
Neural Computing and Applications,
2019
DOI:10.1007/s00521-019-04234-5
|
|
|
|
|
[17]
|
Prediction of Stream Flow in Humid Tropical Rivers by Support Vector Machines
MATEC Web of Conferences,
2017
DOI:10.1051/matecconf/201711101007
|
|
|
|
|
[18]
|
Integrating an artificial intelligence approach with k-means clustering to model groundwater salinity: the case of Gaza coastal aquifer (Palestine)
Hydrogeology Journal,
2017
DOI:10.1007/s10040-017-1658-1
|
|
|
|
|
[19]
|
Prediction of water pollution sources using artificial neural networks in the study areas of Sivas, Karabük and Bartın (Turkey)
Environmental Earth Sciences,
2015
DOI:10.1007/s12665-014-3784-6
|
|
|
|
|
[20]
|
Artificial neural network approach for predicting reverse osmosis desalination plants performance in the Gaza Strip
Desalination,
2015
DOI:10.1016/j.desal.2015.04.008
|
|
|
|
|
[21]
|
Research on Ability Evaluation Model of Compound Talents of Information Technology Based on Artificial Neural Network
2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics,
2013
DOI:10.1109/IHMSC.2013.111
|
|
|
|