Results 231 to 240 of about 2,535,602 (380)

Bayesian Conjugate Analysis for Transition Probabilities of Non-Homogeneous Markov Chain: A Survey [PDF]

, 2014
Minje Sung
openalex   +1 more source

Transfer Learning‐Based Data‐Fusion Model Framework for State of Health Estimation of Power Battery Packs

Battery Energy, EarlyView.
To handle nonlinearity and feature coupling, a data‐driven aging model is proposed, employing dual Gaussian Process Regressions and transfer learning to enhance model efficiency and accuracy. Adaptive filtering refines the model by integrating aging features and output capacity, resulting in a closed‐loop data fusion framework for SOH estimation ...
Zhiqiang Lyu, Xinyuan Wei, Longxing Wu, Chunhui Liu   +3 more
wiley   +1 more source

Iterative hybrid model based optimization of rAAV production

Biotechnology Progress, EarlyView.
Abstract Changes in serotype or genetic payload of recombinant adeno associated virus (rAAVs) gene therapies require adapting the transfection conditions of the upstream HEK293 cultivations. This study adopts an iterative model‐based experiment design approach, where increasing data availability is leveraged to evolve models of different complexity ...
Claudio Müller, Gerald Siegwart, Susanne Heider, Michael Sokolov, Angela Botros, Alexandra Umprecht, Moritz von Stosch, Mariano Nicolas Cruz Bournazou   +7 more
wiley   +1 more source

The probability of reducing hospitalization rates for bronchiolitis with epinephrine and dexamethasone: A Bayesian analysis. [PDF]

PLoS One
Dong L, Klassen TP, Johnson DW, Correll R, Gouin S, Bhatt M, Patel H, Joubert G, Black KJL, Turner TWS, Whitehouse SR, Plint AC, Heath A.   +12 more
europepmc   +1 more source

Consumer Adoption of Internet of Things

Journal of Consumer Behaviour, Volume 24, Issue 2, Page 673-693, March 2025.
ABSTRACT The Internet of Things (IoT), a pivotal technology in enhancing user connectivity, faces a paradox: its widespread potential yet limited consumer adoption. This study addresses this dichotomy by synthesizing a large‐scale meta‐analytic structural equation modeling (MASEM) and hierarchical linear meta‐analysis (HiLMA) of 2736 effect sizes from ...
Wagner Junior Ladeira, Weng Marc Lim, Fernando de Oliveira Santini, Tareq Rasul, Bernardo Frantz, Jean Carlos de Oliveira Rosa, Mohd Azhar   +6 more
wiley   +1 more source

A Bayesian joint probability post-processor for reducing errors and quantifying uncertainty in monthly streamflow predictions

, 2012
Prafulla Pokhrel, David Robertson, Q. J. Wang   +2 more
openalex   +1 more source

Inference on stiffness and strength of existing chestnut timber elements using Hierarchical Bayesian Probability Networks [PDF]

, 2015
Hélder S. Sousa, Jorge M. Branco, Paulo B. Lourénço, Luí­s Neves   +3 more
openalex   +1 more source

Protocol for an Integrative Meta‐Analysis of the Application of Machine Learning Algorithms in the Prediction of Chronic Disease Risks and Outcomes

Chronic Diseases and Translational Medicine, EarlyView.
ABSTRACT Background Precise risk prediction of chronic diseases is essential for effective preventive care and management. Machine learning (ML) is a promising avenue to enhance chronic disease risk prediction; however, a comprehensive assessment of ML performance across various chronic diseases, populations, and health settings is needed. Methods This
Ebenezer Afrifa‐Yamoah, Emmanuel Peprah‐Yamoah, Enoch Odame Anto, Victor Opoku‐Yamoah, Eric Adua   +4 more
wiley   +1 more source

A Snapshot of Bayesianism. [PDF]

Entropy (Basel)
Gannon MA.
europepmc   +1 more source

Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions

Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley   +1 more source