Results 181 to 190 of about 336,714 (315)

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

Fuel-driven hybrid deep learning model for forecasting finger millet prices. [PDF]

Sci Rep
Chaitra B, Meena K.
europepmc   +1 more source

Summary of the RMSE and R² from ridge regression, support vector regression, and random forest based on LOOCV without including the Type as an independent variable. Note: only independent variables were normalized. Asterisks correspond to the highest obtained values with respect to the three models.

Ammar Alsheghri (21011433), Amna Alhammadi (21011436), Vassilis Drakonakis (21011439), Haris Doumanidis (21011442), Imad Barsoum (17178454), Maher Maalouf (6318215)   +5 more
openalex   +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

Rethinking Model Transferability: Validity Domains as a New Approach to Delineate the Limits of Bloom Date Projections. [PDF]

Glob Chang Biol
Bauer JN, Schiffers K, Caspersen L, Yamane H, Luedeling E.   +4 more
europepmc   +1 more source

ANALISIS KEAKURATAN CENTROID MOMENT TENSOR (CMT) PADA SOFTWARE JOKO TINGKIR UNTUK WILAYAH LAUT BANDA MENGGUNAKAN METODE RMSE DAN SUDUT KAGAN

Safirda Adini Rahmatsyah Putri, Muhammad Nurul Fahmi, Madlazim Madlazim   +2 more
openalex   +2 more sources

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Comparison of machine learning models for hemoglobin prediction in patients undergoing maintenance hemodialysis. [PDF]

Front Mol Biosci
Xie T, Su X, Yun C, Tang X, Zheng X, Dong J, Guo Q, Zhu S, Tang D, Dai Y, Yin L.   +10 more
europepmc   +1 more source

In-sample prediction accuracy measures MAE, RMSE, MAPE, and MDA for MKSARMAX, SARMA, SARMAX, additive Holt-Winters, and KARMA models fit of observations from to 102 of the Caconde UV dataset. The best value for each measure is shaded light gray.

Aline Armanini Stefanan (21395087), Murilo Sagrillo (21395090), Bruna G. Palm (21395093), Fábio M. Bayer (9187943)   +3 more
openalex   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source