Results 161 to 170 of about 113,736 (262)

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

An integrated analysis method for critical human factors and paths in hazardous chemical storage accidents based on association rule mining and bayesian networks. [PDF]

PLoS One
Ma S, Jiang W.
europepmc   +1 more source

Risk assessment method on train control system using Bayesian network

, 2013
Che Yulon
openalex   +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

A hybrid framework for disease biomarker discovery in microbiome research combining Bayesian networks, machine learning, and network-based methods. [PDF]

Biol Methods Protoc
Aghdam R, Shan S, Lankau R, Solís-Lemus C.   +3 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

Sensitivity of Bayesian Networks to Errors in Their Structure. [PDF]

Entropy (Basel)
Onisko A, Druzdzel MJ.
europepmc   +1 more source

Analysis of the Influence of Waves in the Occurrence of Accidents in the Portuguese Coast Using Bayesian Belief Networks

, 2010
Pedro Antão, C. Guedes Soares
openalex   +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

Sensitivity of Bayesian Networks to Noise in Their Parameters. [PDF]

Entropy (Basel)
Onisko A, Druzdzel MJ.
europepmc   +1 more source