Results 121 to 130 of about 24,298 (249)

Potential contribution of biomass gasification‐based technology in energy transition: a technical review coupled with bibliometric studies

Biofuels, Bioproducts and Biorefining, EarlyView.
Abstract Biomass gasification technology has been extensively researched around the world; however, there is a need to evaluate the current research landscape and evolutionary direction of research in the broader context of energy transition. A systematic bibliometric analysis of the Web of Science database was performed for articles that fall within ...
Olasunkanmi Opeoluwa Adeoye, Electo Eduardo Silva Lora, Rubenildo Vieira Andrade, Leonardo Peña Pupo, René Lesme Jaén, Osvaldo José Venturini   +5 more
wiley   +1 more source

Applying machine learning to pharmacovigilance data: A proof‐of‐concept study

British Journal of Clinical Pharmacology, EarlyView.
Aim Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance database (FNPV), this proof‐of‐concept study aimed to assess the feasibility of using a ML algorithm—eXtreme Gradient Boosting (XGBoost)—combined with SHapley Additive exPlanations (SHAP) analysis, to ...
Romain Barus, Pauline Schiro, Jean‐Luc Faillie, Romane Freppel, Johana Béné, Claire de Canecaude, François Montastruc   +6 more
wiley   +1 more source

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

Business 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, José Manuel Santos‐Jaén, María Estefanía Sánchez Pacheco, Fernando José Zambrano Farías   +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

Business 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, Mohammadreza Sadeghi‐Moghadam, Hannan Amoozad Mahdiraji   +2 more
wiley   +1 more source

Modelling the impact of dietary diversity on child nutrition in Pakistan: a machine learning analysis with Shapley Additive exPlanations and Boruta interpretability. [PDF]

J Glob Health
Shahid M, Song J, Yahya MA, Dincer H, Yuksel S, Naveed HM, Ali M.   +6 more
europepmc   +1 more source

Do Banks in the Middle East and North Africa Region Price Carbon Exposure?

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines whether carbon exposure is incorporated into corporate borrowing costs within the Middle East and North Africa (MENA) region. Using a panel of 771 firm‐year observations from publicly listed non‐financial firms between 2016 and 2023, the analysis investigates the relationship between carbon intensity and firms' cost of debt
Yara Ibrahim, Khaled Hussainey, Taghred Mokhtar Sayed Moawad   +2 more
wiley   +1 more source

Prediction of atelectasis in <i>Mycoplasma pneumoniae</i> pneumonia using a SHapley Additive exPlanations-interpretable machine learning model. [PDF]

Front Pediatr
Sun J, Wang T, Li M, Wang M.
europepmc   +1 more source

Predicting Environmental Violations: A Cross‐Method Framework Integrating Parametric and Non‐Parametric Approaches

Business Strategy and the Environment, EarlyView.
ABSTRACT Prior research has mostly relied on linear and parametric models while explaining environmental non‐compliance, but they have a limited capacity to capture non‐linear and asymmetric effects of elements affecting firms' environmental compliance.
Ashutosh Singh, Salwa Saleh Almasabi, Ajay Kumar Patel, Judit Petra Koltai, Honghan Qi   +4 more
wiley   +1 more source

Applying gradient tree boosting to QTL mapping with Shapley additive explanations. [PDF]

Breed Sci
Ishibashi T, Onogi A.
europepmc   +1 more source

Using Machine Learning to Predict Corporate Environmental Violation: A Stakeholder Pressure Perspective

Business Strategy and the Environment, EarlyView.
ABSTRACT Predicting corporate environmental violations remains a key challenge in practice and in environmental governance research. However, existing studies have largely focused on ex post associations between stakeholder pressures and realized environmental violations, offering limited insight into whether stakeholder pressures can be used ex ante ...
Xiaolan Chen, Ning Ding, Haodong Jin, Rui Xue, Yuhao Yang   +4 more
wiley   +1 more source