Results 51 to 60 of about 9,138 (211)
Implicit-Causality-Exploration-Enabled Graph Neural Network for Stock Prediction
Accurate stock prediction plays an important role in financial markets and can aid investors in making well-informed decisions and optimizing their investment strategies.
Ying Li +4 more
doaj +1 more source
ABSTRACT Drought is among the most severe and persistent threats to food supply chains, and relocating production to less drought‐prone regions offers a strategy to reduce this risk. This is particularly relevant for fresh vegetables, which are highly water‐intensive, yet drought‐driven reconfiguration strategies remain understudied.
Bingyan Dai +2 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang +6 more
wiley +1 more source
Time‐Delayed Spiking Reservoir Computing Enables Efficient Time Series Prediction
This study proposes time‐delayed spiking reservoir computing (TDSRC) for efficient time series prediction. By concatenating time‐lagged states, TDSRC constructs an expanded readout feature vector without altering internal reservoir dynamics. This approach enables highly accurate forecasting with significantly fewer neurons, providing a resource ...
Pin Jin +3 more
wiley +1 more source
Big Trajectory Data: A Survey of Applications and Services
The rapid development of wireless infrastructure and data acquisition technologies contributes to the explosive growth of data, especially trajectory data with rich information.
Xiangjie Kong +6 more
doaj +1 more source
Abstract This study examines the impact of soil erosion on agricultural land values in the United States (US) Midwest. Based on a novel county‐level panel data set with information on soil erosion levels and agricultural land values covering five census years (1997, 2002, 2007, 2012, and 2017), we separately investigate the direct effect of two types ...
Le Chen +3 more
wiley +1 more source
Study on Nuclear Accident Precursors Using AHP and BBN
Most of the nuclear accident reports used to indicate the implicit precursors which are not easily quantified as underlying factors. The current Probabilistic Safety Assessment (PSA) is capable of quantifying the importance of accident causes in limited ...
Sujin Park +4 more
doaj +1 more source
Accounting for animal health in efficiency analysis: An application to Swedish dairy farms
Abstract Poor animal health is a central concern in modern livestock production. Despite the necessity to incorporate animal health in efficiency analysis, the theoretical and empirical developments are limited on this subject. This article appropriately characterizes the axiomatic properties of animal health within a production framework.
Frederic Ang +3 more
wiley +1 more source

