Results 171 to 180 of about 4,539 (295)

Explainable hybrid stacking ensemble method for hard rock pillar stability prediction and engineering applications

open access: yesDeep Underground Science and Engineering, EarlyView.
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang   +3 more
wiley   +1 more source

TAMNet: Temporal and adaptive‐frequency network with MixStyle for cross‐region oil and fluid production forecasting

open access: yesDeep Underground Science and Engineering, EarlyView.
This paper presents temporal and adaptive‐frequency network with MixStyle (TAMNet), a deep time‐series modeling framework for accurate and robust multi‐well oil productivity forecasting. TAMNet integrates transformer and long short‐term memory architectures to capture both short‐ and long‐term temporal dependencies, enhanced by a temporal gate unit ...
Chunxi Yang   +6 more
wiley   +1 more source

Preparatory phase of large earthquakes illuminated by unsupervised categorization of earthquake catalog features. [PDF]

open access: yesNat Commun
Karimpouli S   +8 more
europepmc   +1 more source

Investigation on the failure evolution characteristics of surrounding rock in deep cross‐fault roadway: Based on physical model test and numerical simulation

open access: yesDeep Underground Science and Engineering, EarlyView.
This study reveals the failure evolution characteristics of deep cross‐fault roadway surrounding rock under excavation support and periodic weighting. Periodic weighting readily induces fault activation, with the spatial distribution of failed rock masses being controlled by the fault strike and dip.
Tiezhu Li   +4 more
wiley   +1 more source

Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning. [PDF]

open access: yesNat Commun
Lyu D   +6 more
europepmc   +1 more source

Climatic drivers prevail in montane and lowland Odonata latitudinal diversity gradients, but human modification erodes lowland patterns

open access: yesEcography, EarlyView.
Latitudinal diversity gradients (LDGs) arise from the interplay of historical, ecological, and evolutionary processes, yet these drivers may differ across landforms. Mountains, with steep elevational and climatic gradients, often sustain distinct diversity dynamics compared with adjacent lowlands, where vertical climatic gradients are weak and human ...
Zhenyuan Liu   +5 more
wiley   +1 more source

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