Results 191 to 200 of about 331,059 (292)

Mathematical modelling and simulation of the road traffic : statistical analysis of merging models and probabilistic simulation of a kinetic model

, 2014
La première partie de cette thèse a consisté à proposer des modèles d'insertion de trafic sur une bretelle d'entrée d'autoroute. Deux types de modélisation ont été élaborés. Une approche statistique utilisant les techniques de régression logistique nous a permis de sélectionner les variables jouant un rôle dans le choix par les véhicules provenant de ...
openaire   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Unveiling toxicological adverse outcomes: toward construction and simulation of large-scale networks. [PDF]

Toxicol Sci
Ikonomi N, Ketter N, Pepe MAA.
europepmc   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

A hybrid STL-LightGBM framework with probabilistic forecasting for Influenza A incidence in the post-pandemic Saudi Arabia. [PDF]

Front Public Health
Alahmadi RM, Awadalla M, Saeed B, Alshanbari HM, Shokeralla AA, Yassin AA, Alosaimi B, Guma FE.   +7 more
europepmc   +1 more source

Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns

Advanced Intelligent Discovery, EarlyView.
Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer, André Orth, Robert Wang, Ben Breitung, Simon Schweidler, Jasmin Aghassi‐Hagmann, Markus Reischl   +6 more
wiley   +1 more source

A non-parametric adaptive conformal inference based probabilistic hour-ahead solar PV power forecasting method. [PDF]

Sci Rep
Suresh V, Revathi BS, Guerrero JM.
europepmc   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Optimized decomposition and deep learning with bias correction for reliable runoff point-interval prediction. [PDF]

Sci Rep
Ma H, Marsani MF, Mansor MA, Kasihmuddin MSM, Long C.   +4 more
europepmc   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source