Results 171 to 180 of about 44,463 (307)

SHAP Job Burnout Prediction Dataset and Materials"

open access: yes
Synthetic dataset and Python materials for demonstrating SHAP-based machine learning interpretation of job burnout predictors, as described in Weiser (2025).
Eric B Weiser
core   +1 more source

Do Governance Structures Drive Green Building Adoption? A Machine Learning Approach With Random Forests

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT This study examines the determinants of firms' propensity to adopt green buildings in the Euro Stoxx 300 and the S&P 500 indices, during 2012–2023. Using random forest binary classifiers, we assess the relative importance of financial, sectoral, geographic, and climate governance predictors and uncover nonlinear relationships often overlooked ...
María del Carmen Valls Martínez   +3 more
wiley   +1 more source

An Indicator‐Based Decision Framework for Circular Bioeconomy Transition in the Steel Industry: Integrating Multiphase Learning and Cooperative Game Modelling

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT Despite growing attention to the circular bioeconomy (CBE), the steel industry currently lacks a standardised, sectoral measurement framework to facilitate a low‐carbon transition. In this study, a decision‐support framework for evaluating CBE performance in the steel industry is proposed.
Ali Zamani Babgohari   +2 more
wiley   +1 more source

Explainable time-series forecasting with sampling-free SHAP for Transformers. [PDF]

open access: yesNat Commun
Hertel M   +4 more
europepmc   +1 more source

Analysis of Ruddlesden‐Popper and Dion‐Jacobson 2D Lead Halide Perovskites Through Integrated Experimental and Computational Analysis

open access: yesBattery Energy, Volume 4, Issue 2, March 2025.
Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley   +1 more source

Machine learning‐assisted clone selection for intensified cell culture processes

open access: yesBiotechnology Progress, EarlyView.
Abstract Intensified fed‐batch processes are becoming increasingly prevalent among biomanufacturers due to their superior space–time yields relative to traditional, non‐intensified fed‐batch processes. However, the shift towards intensified manufacturing has unexpectedly made optimal clone selection more challenging.
Nicolas Wolnick   +6 more
wiley   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

open access: yesCarbon and Hydrogen, EarlyView.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao   +6 more
wiley   +1 more source

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