Mapping and modeling groundwater potential using machine learning, deep learning and ensemble learning models in the Saiss basin (Fez-Meknes region, Morocco …
The Saïss basin in the Fez-Meknes region of Morocco, covering approximately 2100 km 2,
faces increased water demand due to population growth, economic development, and …
faces increased water demand due to population growth, economic development, and …
Effects of DEM resolution and application of solely DEM-derived indicators on groundwater potential mapping in the mountainous area
Groundwater potential mapping (GWPM) enables to efficiently support sustainable
groundwater management activities such as monitoring, exploitation, conservation, and …
groundwater management activities such as monitoring, exploitation, conservation, and …
Identifying factors influencing reservoir eutrophication using interpretable machine learning combined with shoreline morphology and landscape hydrological features …
C Shi, N Zhuang, Y Li, J Xiong, Y Zhang, C Ding… - Science of The Total …, 2024 - Elsevier
Reservoir nearshore areas are influenced by both terrestrial and aquatic ecosystems,
making them sensitive regions to water quality changes. The analysis of basin landscape …
making them sensitive regions to water quality changes. The analysis of basin landscape …
Groundwater sustainability assessment and the research-practice nexus
BA Ashtiani, CT Simmons, L Farhadi, S Zhang - Journal of Hydrology, 2024 - Elsevier
Over the past decade, significant advancements in research and technology have greatly
improved data collection, transfer, storage, and assimilation, as well as the development of …
improved data collection, transfer, storage, and assimilation, as well as the development of …
[HTML][HTML] Fusion of GIS, remote sensing, geophysics and Dempster Shafer theory of evidence for mapping groundwater prospectivity: A case study of the central parts of …
Water utilization for different human activities is universally crucial, but it is not readily
available for consumption in some areas, such as the central parts of Lagos State, Nigeria …
available for consumption in some areas, such as the central parts of Lagos State, Nigeria …
Value-at-Risk forecasting for the Chinese new energy stock market: an explainable quantile regression neural network method
X Wang, H Liu, Y Yao - Procedia Computer Science, 2024 - Elsevier
This study utilizes the quantile regression neural network (QRNN) model to forecast the
Value-at-Risk (VaR) of ten new energy stock markets by considering ten influencing factors …
Value-at-Risk (VaR) of ten new energy stock markets by considering ten influencing factors …