Results 111 to 120 of about 776,810 (287)

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Explainable artificial intelligence (XAI) for interpreting predictive models and key variables in flood susceptibility

Results in Engineering
The black-box nature of machine learning limits its explainability and practical application. This study highlights the importance of enhancing interpretability in flood modeling and prediction by investigating the interactions between flood-related ...
Bahram Choubin, Abolfazl Jaafari, Jalal Henareh, Omid Karimi, Farzaneh Sajedi Hosseini   +4 more
doaj   +1 more source

New Axiomatizations and an Implementation of the Shapley Value [PDF]

Some new axiomatic characterizations and recursive formulas of the Shapley value are presented. In the results, dual games and the self-duality of the value implicitly play an important role.
Kongo, T., Tijs, S.H., Funaki, Y.
core  

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Dividends and Weighted Values in Games with Externalities [PDF]

We consider cooperative environments with externalities (games in partition function form) and provide a recursive definition of dividends for each coalition and any partition of the players it belongs to.
David Wettstein, David Perez-Castrillo, Ines Macho-Stadler   +2 more
core  

What Really Drives Agri‐Environment‐Climate Measures' Adoption? Mandatory Requirements, Behavioral Traits, and Structural Factors in the CAP Green Architecture

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT To increase farmer adoption of green practices, the EU Common Agricultural Policy includes both mandatory (conditionality) and voluntary instruments (eco‐schemes–ECS– and more demanding, multi‐annual agri‐environment‐climate measures –AECM–). Building on the experiment of Barreiro‐Hurle et al.
L. Sanchez‐Mata, M. Rodríguez‐Entrena, M. Espinosa‐Goded, F. J. Dessart, J. Barreiro‐Hurlé   +4 more
wiley   +1 more source

Efficient Computation of the Shapley Value for Centrality in Networks

, 2010
The Shapley Value is arguably the most important normative solution concept in coalitional games. One of its applications is in the domain of networks, where the Shapley Value is used to measure the relative importance of individual nodes.
Michalak, Tomasz P., Ravindran, Balaraman, Aadithya, Karthik V., Jennings, Nicholas R.   +3 more
core   +2 more sources

Regional Brain Aging Disparity Index: Region-Specific Brain Aging State Index for Neurodegenerative Diseases and Chronic Disease Specificity

Bioengineering
This study proposes a novel brain-region-level aging assessment paradigm based on Shapley value interpretation, aiming to overcome the interpretability limitations of traditional brain age prediction models.
Yutong Wu, Shen Sun, Chen Zhang, Xiangge Ma, Xinyu Zhu, Yanxue Li, Lan Lin, Zhenrong Fu   +7 more
doaj   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Predicting Consumer Electronics E-Commerce: Technology Acceptance Model and Logistics Service Quality.

International Journal of Interactive Multimedia and Artificial Intelligence
In online shopping for consumer electronics, information and physical flows are crucial determinants of consumer purchase intentions. This study examines these factors by integrating the Technology Acceptance Model with logistics service ...
Cheng Feng Wu, Kunkun Zhang, Meng Chen Lin, Chei Chang Chiou   +3 more
doaj   +1 more source