Results 171 to 180 of about 3,905,952 (289)

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

Uncertainty estimation and probabilistic skull shape reconstruction using bayesian neural networks. [PDF]

Sci Rep
Li J, Sengupta A, Zachow S.
europepmc   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Bayesian neural networks with variable selection for prediction of genotypic values. [PDF]

Genet Sel Evol, 2020
van Bergen GHH, Duenk P, Albers CA, Bijma P, Calus MPL, Wientjes YCJ, Kappen HJ.   +6 more
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

Deep bayesian neural networks for UWB phase error correction in positioning systems. [PDF]

Sci Rep
Li J, Yu B, Yang M, Zhao J, Cui S, Tian R, Bao Y.   +6 more
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Ferroelectric NAND for efficient hardware bayesian neural networks. [PDF]

Nat Commun
Song M, Koo RH, Kim J, Han CH, Yim J, Ko J, Yoo S, Choe DH, Kim S, Shin W, Kwon D.   +10 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Uncertainty-Aware Parking Prediction Using Bayesian Neural Networks. [PDF]

Sensors (Basel)
Nezhadettehad A, Zaslavsky A, Rakib A, Loke SW.   +3 more
europepmc   +1 more source