Results 81 to 90 of about 24,298 (249)

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

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

Exploring the Pedestrian Route Choice Behaviors by Machine Learning Models

ISPRS International Journal of Geo-Information
To investigate pedestrian route choice mechanisms from a perspective distinct from that employed in discrete choice models (DCMs), this study utilizes machine learning models and employs SHapley Additive exPlanations (SHAP) for model interpretation.
Cheng-Jie Jin, Yuanwei Luo, Chenyang Wu, Yuchen Song, Dawei Li   +4 more
doaj   +1 more source

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

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

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

Annals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

Predicting travel mode choice with a robust neural network and Shapley additive explanations analysis

IET Intelligent Transport Systems
Predicting and understanding travellers’ mode choices is crucial to developing urban transportation systems and formulating traffic demand management strategies. Machine learning (ML) methods have been widely used as promising alternatives to traditional
Li Tang, Chuanli Tang, Qi Fu, Changxi Ma
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

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

Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity

Unsupervised anomaly detection is a challenging problem due to the diversity of data distributions and the lack of labels. Ensemble methods are often adopted to mitigate these challenges by combining multiple detectors, which can reduce individual biases and increase robustness.
Jordan Levy, Paul Saves, Moncef Garouani, Nicolas Verstaevel, Benoit Gaudou   +4 more
openaire   +2 more sources