Results 51 to 60 of about 776,810 (287)

Explainable deep learning with Shapley additive explanations for multivariate wind power forecasting

Energy Conversion and Management: X
Wind is a popular renewable energy source, but it is highly dependent on environmental conditions and internal dynamics. Given these complexities, the need for accurate forecasting models that account for multiple variables is critical.
Ege Kandemir, Dilip Kumar Prasad, Agus Hasan, Trond Kvamsdal, Saleh Abdel-Afou Alaliyat   +4 more
doaj   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Landslide Modeling in a Tropical Mountain Basin Using Machine Learning Algorithms and Shapley Additive Explanations

Air, Soil and Water Research, 2023
Landslides are a geological hazard commonly induced by rainfall, earthquakes, deforestation, or human activity causing loss of human life every year specially on highlands or mountain slopes with serious impacts that threaten communities and its ...
Johnny Vega, Fabio Humberto Sepúlveda-Murillo, Melissa Parra   +2 more
doaj   +1 more source

Leveraging Data‐Driven and Fundamental Insights for Electrolyte Innovation in Lithium Metal Batteries

Advanced Materials, EarlyView.
Using 640 curated electrolyte formulations, we apply data‐driven analysis to reveal how molecular features govern coulombic efficiency (CE) in lithium metal batteries. Fluorine content correlates positively with CE, while oxygen, carbon, and higher boiling points correlate negatively.
Minh Van Duong, Mitchell Kaiser, Xia Cao, Trung Thien Nguyen, Au Nguyen, Phung My Loan Le, Jun Liu   +6 more
wiley   +1 more source

Interpretable machine learning with tree-based shapley additive explanations: Application to metabolomics datasets for binary classification.

PLoS ONE, 2023
Machine learning (ML) models are used in clinical metabolomics studies most notably for biomarker discoveries, to identify metabolites that discriminate between a case and control group.
Olatomiwa O Bifarin
doaj   +1 more source

Calculation of exact Shapley values for support vector machines with Tanimoto kernel enables model interpretation

iScience, 2022
Summary: The support vector machine (SVM) algorithm is popular in chemistry and drug discovery. SVM models have black box character. Their predictions can be interpreted through feature weighting or the model-agnostic Shapley additive explanations (SHAP)
Christian Feldmann, Jürgen Bajorath
doaj   +1 more source

Angled Nozzle Aerosol Jet Printing to Streamline Conformal Patterning of Electronics

Advanced Materials Technologies, EarlyView.
A modular, angled aerosol jet printhead is demonstrated to streamline patterning on nonplanar surfaces, including 90° step edges and confined internal geometries. A detailed analysis of gravitational settling for a sheathed aerosol flow and deconvolution of oblique deposition and gravitational effects supports the versatility of this approach for ...
Louis O. Morgan, Jeremy D. Rurup, Hal K. Griswold, Md Ramjan Ali, Ethan B. Secor   +4 more
wiley   +1 more source

Evaluation of the Shapley Additive Explanation Technique for Ensemble Learning Methods

Proceedings of Engineering and Technology Innovation, 2022
This study aims to explore the effectiveness of the Shapley additive explanation (SHAP) technique in developing a transparent, interpretable, and explainable ensemble method for heart disease diagnosis using random forest algorithms. Firstly, the features with high impact on the heart disease prediction are selected by SHAP using 1025 heart disease ...
openaire   +1 more source

Comparing Baseline Shapley and Integrated Gradients for Local Explanation: Some Additional Insights

CoRR, 2022
There are many different methods in the literature for local explanation of machine learning results. However, the methods differ in their approaches and often do not provide same explanations. In this paper, we consider two recent methods: Integrated Gradients (Sundararajan, Taly, & Yan, 2017) and Baseline Shapley (Sundararajan and Najmi, 2020 ...
Tianshu Feng, Zhipu Zhou, Tarun Joshi, Vijayan N. Nair   +3 more
openaire   +3 more sources