Results 111 to 120 of about 11,307,335 (373)

Accelerated Screening of Halide Double Perovskites via Hybrid Density Functional Theory and Machine Learning for Thermoelectric Energy Conversion

open access: yesAdvanced Energy and Sustainability Research, EarlyView.
This study integrates hybrid density functional theory, Boltzmann transport theory, and machine learning to accelerate the discovery of lead‐free halide double perovskites for thermoelectric energy conversion. By screening 102 compounds, the authors identify high‐performing candidates such as Rb2GeI6 and Cs2SnBr6, offering a sustainable pathway toward ...
Souraya Goumri‐Said   +2 more
wiley   +1 more source

An Ordinal Shapley Value for Economic Environments (Revised Version) [PDF]

open access: yes
We propose a new solution concept to address the problem of sharing a surplus among the agents generating it. The problem is formulated in the preferences-endowments space.
David Perez-Castrillo, David Wettstein
core  

Associated consistency and values for TU games [PDF]

open access: yes, 2006
In the framework of the solution theory for cooperative transferable utility games, Hamiache axiomatized the well-known Shapley value as the unique one-point solution verifying the inessential game property, continuity, and associated consistency.
T. S. H. Driessen, Theo Driessen
core   +2 more sources

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

open access: yesAdvanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang   +5 more
wiley   +1 more source

Analyzing cooperative game theory solutions: core and Shapley value in cartesian product of two sets

open access: yesFrontiers in Applied Mathematics and Statistics
The core and the Shapley value stand out as the most renowned solutions for addressing sharing problems in cooperative game theory. These concepts are widely acknowledged for their effectiveness in tackling negotiation, resource allocation, and power ...
Mekdad Slime   +2 more
doaj   +1 more source

Implementation of the Ordinal Shapley Value for a three-agent economy [PDF]

open access: yes
We propose a simple mechanism that implements the Ordinal Shapley Value (Pérez-Castrillo and Wettstein [2005]) for economies with three or less agents.Ordinal Shapley Value, implementation, mechanism ...
David Pérez-Castrillo, David Wettstein
core  

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

open access: yesAdvanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar   +3 more
wiley   +1 more source

Applications of Shapley Value to Financial Decision-Making and Risk Management

open access: yesAppliedMath
We investigate the application of the Shapley value in addressing risk-related challenges, focusing on two primary areas. The first area explores the role of the Shapley value in the financial sector, specifically in managing portfolio risk.
Sunday Timileyin Ayodeji   +2 more
doaj   +1 more source

Uncertainty of the Shapley Value [PDF]

open access: yes
This paper introduces a measure of uncertainty in the determination of the Shapley value, illustrates it with examples, and studies some of its properties.
Vladislav Kargin
core  

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

open access: yesAdvanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia   +3 more
wiley   +1 more source

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