Subsurface sedimentary structure identification using deep learning: A review
The reliable identification of subsurface sedimentary structures (ie, geologic heterogeneity)
is critical in various earth and environmental sciences, petroleum reservoir engineering, and …
is critical in various earth and environmental sciences, petroleum reservoir engineering, and …
Soil moisture measuring techniques and factors affecting the moisture dynamics: A comprehensive review
The amount of surface soil moisture (SSM) is a crucial ecohydrological natural resource that
regulates important land surface processes. It affects critical land–atmospheric phenomena …
regulates important land surface processes. It affects critical land–atmospheric phenomena …
Data‐worth analysis for heterogeneous subsurface structure identification with a stochastic deep learning framework
Reliable characterization of subsurface structures is essential for earth sciences and related
applications. Data assimilation‐based identification frameworks can reasonably estimate …
applications. Data assimilation‐based identification frameworks can reasonably estimate …
A deep learning-based data-driven approach for predicting mining water inrush from coal seam floor using micro-seismic monitoring data
H Yin, G Zhang, Q Wu, S Yin… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
Microseismic monitoring during mining operations generates spatiotemporal data that could
indicate strata fractures and deformations leading to water inrush anomalies. However …
indicate strata fractures and deformations leading to water inrush anomalies. However …
Flash flood susceptibility assessment and zonation by integrating analytic hierarchy process and frequency ratio model with diverse spatial data
Flash floods are the most dangerous kinds of floods because they combine the destructive
power of a flood with incredible speed. They occur when heavy rainfall exceeds the ability of …
power of a flood with incredible speed. They occur when heavy rainfall exceeds the ability of …
Robust runoff prediction with explainable artificial intelligence and meteorological variables from deep learning ensemble model
J Wu, Z Wang, J Dong, X Cui, S Tao… - Water Resources …, 2023 - Wiley Online Library
Accurate runoff forecasting plays a vital role in issuing timely flood warnings. Whereas,
previous research has primarily focused on historical runoff and precipitation variability …
previous research has primarily focused on historical runoff and precipitation variability …
Retracted: Enhancing waste management and prediction of water quality in the sustainable urban environment using optimized algorithm of least square support …
Following an investigation into a number of papers published as part of the Urban
Groundwater Special Issue in Urban Climate, it became evident that the names of two co …
Groundwater Special Issue in Urban Climate, it became evident that the names of two co …
[HTML][HTML] A hybrid physics-informed data-driven neural network for CO2 storage in depleted shale reservoirs
YW Wang, ZX Dai, GS Wang, L Chen, YZ ** (LSM) of Swat District, Hindu Kush Himalayan region of Pakistan, using GIS-based bivariate modeling
Landslides are a recurrent environmental hazard in hilly regions and affect the
socioeconomic development in Pakistan. The current study area is the tourism and hydro …
socioeconomic development in Pakistan. The current study area is the tourism and hydro …