Results 221 to 230 of about 118,631 (311)
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 +8 more
wiley +1 more source
Evaluating athletic mental energy analysis: a novel approach using fuzzy-based Bayesian networks. [PDF]
Yildiz Y +3 more
europepmc +1 more source
Prior Performance and Risk-Taking of Mutual Fund Managers: A Dynamic Bayesian Network Approach
Manuel Ammann, Michael Verhofen
openalex +1 more source
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 +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]
Ma S, Jiang W.
europepmc +1 more source
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]
Aghdam R +3 more
europepmc +1 more source
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]
Onisko A, Druzdzel MJ.
europepmc +1 more source

