Results 71 to 80 of about 44,463 (307)

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

Unveiling financial well-being: Insights from retired people in Third Age group in Poland, Spain and Denmark

Economics and Business Review
The study investigates the financial well-being of older people in Poland, Spain and Denmark, with a particular focus on their ability to make ends meet.
Jajko-Siwek Alicja
doaj   +1 more source

The use of ICTs and income distribution in Brazil: A machine learning explanation using SHAP values

, 2023
This study explores the complex relationship between information and communication technologies (ICTs) and socioeconomic characteristics. We employ a cutting-edge explainable machine learning approach, known as SHAP values, to interpret an XGBoost and ...
Herrera, GP, Su, JJ, Athula Naranpanawa, Gabriel Paes Herrera, Constantino, M, Naranpanawa, A, Michel Constantino, Jen-Je Su   +7 more
core   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Análisis de licitaciones públicas en Ecuador: aplicación de técnicas de explicabilidad en modelos de aprendizaje automático

Revista Odigos
Las licitaciones públicas permiten a las instituciones contratar bienes, obras y servicios esenciales para el crecimiento del país. Este trabajo consistió en analizar los procesos de licitaciones públicas en Ecuador mediante la aplicación de técnicas de ...
Maria Fernanda Molina Miranda, Ángel Cuenca Ortega, Luis Espín Pazmiño, Miguel Molina Villacís   +3 more
doaj   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

АВТОМАТИЗОВАНЕ ВИЯВЛЕННЯ АНОМАЛІЙ У ТРАФІКУ КОРПОРАТИВНИХ БЕЗДРОТОВИХ МЕРЕЖ ЗА ДОПОМОГОЮ PYTHON: МЕТОДИ, РЕАЛІЗАЦІЯ ТА ОЦІНКА ЕФЕКТИВНОСТІ

Кібербезпека: освіта, наука, техніка
Представлено результати дослідження, присвяченого розробці та порівнянню моделей автоматизованого виявлення аномалій у трафіку корпоративних бездротових мереж.
Ізабелла Соболенко, Артем Платоненко   +1 more
doaj   +1 more source

Shap-Select: Lightweight Feature Selection Using SHAP Values and Regression

CoRR
Feature selection is an essential process in machine learning, especially when dealing with high-dimensional datasets. It helps reduce the complexity of machine learning models, improve performance, mitigate overfitting, and decrease computation time. This paper presents a novel feature selection framework, shap-select.
Egor Kraev, Baran Koseoglu, Luca Traverso, Mohammed Topiwalla   +3 more
openaire   +2 more sources

SHAP for resting BS.

, 2023
Each point represents each observation; the red line represents a trend line. X-axis is the covariate of interest, Resting Blood Pressure (mean arterial pressure). The SHAP value represents the log-odds for heart disease. (TIF)
Samuel Y. Huang (14670660), Alexander A. Huang (14670657)   +1 more
core   +1 more source

Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

Advanced Science, EarlyView.
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang, Ziyuan Li, Shan Gao, Zhen Zhu, Jing Wang, Xiangmei Duan   +5 more
wiley   +1 more source