Results 161 to 170 of about 624,838 (295)

A general framework for adaptive nonparametric dimensionality reduction. [PDF]

Sci Rep
Di Noia A, Ravenda F, Mira A.
europepmc   +1 more source

Price Transmission and Leadership in the Global Poultry Market: Results From Parametric and Nonparametric Approaches

Agribusiness, EarlyView.
ABSTRACT Brazil and the United States account for more than 40% of global poultry exports, with China and South Korea among their major destination markets. This study examines price transmission and market linkages between Brazil and the United States using monthly poultry export price data from January 1990 to December 2024. It also assesses which of
Khondoker Abdul Mottaleb, Shaikh M. Rahman, Syed Imran Ali Meerza   +2 more
wiley   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Advanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai, Wenrui Wang, Rui Chen, Tong Yu, Xiaojuan Zheng, Hua Shao, Dashan Shang, Ling Li, Lado Filipovic   +8 more
wiley   +1 more source

Nonparametric quantile regression captures regional variability and scaling deviations in Atlantic surfclam length-weight relationships. [PDF]

Sci Rep
Bidegain G, Sestelo M, Luque PL, Powell EN, Irirarte A, Uriarte I, Munroe D.   +6 more
europepmc   +1 more source

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas. [PDF]

Entropy (Basel)
Desuó Neto L, de Oliveira Caetano H, de Souza Sant'Anna Fogliatto M, Dias Maciel C.   +3 more
europepmc   +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

Modeling insurance claims using Bayesian nonparametric regression. [PDF]

PLoS One
Shams M, Ghosh K.
europepmc   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Estimation of space-time self-exciting point process models using multi-dimensional Gaussian-type exponent approximation. [PDF]

PLoS One
Nketiah EA, Li C, Yang W, Jing Y, Guo P.
europepmc   +1 more source