All systems operational
Q1 2026

Spatiotemporal prediction and predictive management of foundation Pit groundwater levels under multi-source disturbance: A data-driven deep learning approach

Shuhong Wang · Shuo Zhang · Hong Yin · Zhiqiang Huang
10.1016/j.aej.2026.05.014 382 Views 0 Citations
0
Citations
382
Views
Abstract not available for this publication.
Cite this Article (APA)
Shuhong, W., Shuo, Z., Hong, Y., Zhiqiang, H. (2026). Spatiotemporal prediction and predictive management of foundation Pit groundwater levels under multi-source disturbance: A data-driven deep learning approach. Alexandria Engineering Journal. https://doi.org/10.1016/j.aej.2026.05.014
Related Papers
On the stochastic simulation by optimal control and bifurcation analysis of the computer virus model…
Emad Solouma; Mansoor Alsulami; Haci Mehmet Baskonus; A.F. Aljohani; Sayed Saber · 2026
7
cites
398
3
cites
397
Experimental study on SDBS surfactant effect on titanium oxide water nanofluid properties
George Cătălin TOFAN; Bogdan PRICOP; Cătălin Andrei ŢUGUI; Alina Adriana MINEA · 2026
2
cites
396
Access
View Full Text via DOI
Published in
ISSN 1110-0168
Quartile Q1
AMS Score 100
Field Engineering & Technology
Publisher Elsevier / Alexandria University
Country 🇪🇬 Egypt
View Journal Profile →
Authors
Publication Details
Year 2026
Language English
Added 27 Jul 2026