Machine learning (ML) is widely used in many industries, resulting in recent interests to
explore ML in geotechnical engineering. Past review papers focus mainly on ML algorithms …

Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …

Recently, integrated machine learning (ML) metaheuristic algorithms, such as the artificial
bee colony (ABC) algorithm, genetic algorithm (GA), gray wolf optimization (GWO) algorithm …

Abstract Machine learning (ML) has been extensively applied to model geohazards, yielding
tremendous success. However, researchers and practitioners still face challenges in …

强震诱发的滑坡具有数量多, 分布广, 规模大等特点, 严重威胁人民生命财产安全.
滑坡易发性评价能够快速预测灾害空间分布, 对于减轻震后灾害的危险性具有重要意义 …

Abstract The Three Gorges Reservoir Area (TGRA) is one of the most important landslide-
prone regions in China, and rational stability evaluation of reservoir slopes in it is of great …

Earth system modelling (ESM) is essential for understanding past, present and future Earth
processes. Deep learning (DL), with the data-driven strength of neural networks, has …

Frequent forest fires are causing severe harm to the natural environment, such as
decreasing air quality and threatening different species; therefore, developing accurate …

With shrinking natural resources and the climate challenges, it is foreseen that there will be
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …

Easy and efficient acquisition of high-resolution remote sensing images is of importance in
geographic information systems. Previously, deep neural networks composed of …