Results 191 to 200 of about 22,620 (225)

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Density clustering based fast and stable satellite selection for LEO navigation. [PDF]

Sci Rep
Lu Z, Zhang S, Wang Y, Xiong J, Zhao R.
europepmc   +1 more source

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

Chaos-Embedded Multi-Objective Intelligent Optimization-Based Explainable Classification Model for Determining Cherry Fruit Fly Infestation Levels Using Pomological Data. [PDF]

Biomimetics (Basel)
Yildirim S, Ozgen I, Alatas B, Yildirim H.   +3 more
europepmc   +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

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Uncertainty-Aware adaptive neuro-fuzzy transformer framework for robust multi-center lung disease classification. [PDF]

Sci Rep
Dahan F, Shah JH, Alfakih TM, Farooq H, Aloqaily M, Alshammari M.   +5 more
europepmc   +1 more source

Source camera attribution using a rule-based explainable convolutional neural network. [PDF]

Sci Rep
Nayerifard T, Amintoosi H, Ghaemi Bafghi A.   +2 more
europepmc   +1 more source

An Early Trial-Based Cost-Effectiveness Analysis of Extracorporeal Shockwave Therapy for Diabetes Related Foot Ulcer Healing. [PDF]

Int Wound J
Hitchman L, Siciliano M, Lathan R, Ravindhran B, Sidapra M, Long J, Smith G, Twiddy M, Russell D, Chetter IC, Iglesias Urrutia C.   +10 more
europepmc   +1 more source