Data Science | Environmental Science | Hydrology Using an interpretable deep learning model for the prediction of riverine suspended sediment load. April 24, 2024
Data Science | Earth Science | Geology An interpretable deep learning model to map land subsidence hazard. February 10, 2024
Air Quality Management | Environmental Science Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind. December 7, 2023
Environmental Science | Geosciences Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion. September 11, 2023
Environmental Science | Geography | Hydrology Novel integrated modelling based on multiplicative long short-term memory (mLSTM) deep learning model and ensemble multi-criteria decision making (MCDM) models for mapping flood risk. August 18, 2023
Geology | Hydrogeology Stacking- and voting-based ensemble deep learning models (SEDL and VEDL) and active learning (AL) for mapping land subsidence. November 12, 2022
Climate science | Data Science | Environmental Science Novel deep learning hybrid models (CNN-GRU and DLDL-RF) for the susceptibility classification of dust sources in the Middle East: a global source. November 12, 2022
Other Assessment of the uncertainty and interpretability of deep learning models for mapping soil salinity using DeepQuantreg and game theory. September 7, 2022
Environmental Sciences | Soil Science | Spatial Modelling Spatial modelling of soil salinity: deep or shallow learning models? March 24, 2021