Results 71 to 80 of about 125,648 (258)

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Pushing for the Extreme: Estimation of Poisson Distribution from Low Count Unreplicated Data—How Close Can We Get?

Entropy, 2013
Studies of learning algorithms typically concentrate on situations where potentially ever growing training sample is available. Yet, there can be situations (e.g., detection of differentially expressed genes on unreplicated data or estimation of time ...
Peter Tiňo
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Improving maximum likelihood estimation using prior probabilities: A tutorial on maximum a posteriori estimation and an examination of the weibull distribution [PDF]

Tutorials in Quantitative Methods for Psychology, 2013
This tutorial describes a parameter estimation technique that is little-known in social sciences, namely maximum a posteriori estimation. This technique can be used in conjunction with prior knowledge to improve maximumlikelihood estimation of the best ...
Denis Cousineau, Sebastien Helie
doaj  

Bayesian Methods for Predicting the Shape of Chinese Yam in Terms of Key Diameters

Advances in Agriculture, 2017
This paper proposes Bayesian methods for the shape estimation of Chinese yam (Dioscorea opposita) using a few key diameters of yam. Shape prediction of yam is applicable to determining optimal cutoff positions of a yam for producing seed yams.
Mitsunori Kayano, Koki Kyo, Mitsuru Hachiya   +2 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Comparison of some Bayesian estimation methods for type-I generalized extreme value distribution with simulation

Alexandria Engineering Journal
The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play
Sundos Bader Habeeb, Fatima K. Abdullah, Rehab Noori Shalan, Amal S. Hassan, Ehab M. Almetwally, Fatimah M. Alghamdi, Sara Mohamed Ahmed Alsheikh, Md Moyazzem Hossain   +7 more
doaj   +1 more source

Bayesian Quantum Amplitude Estimation [PDF]

Quantum
We present BAE, a problem-tailored and noise-aware Bayesian algorithm for quantum amplitude estimation. In a fault tolerant scenario, BAE is capable of saturating the Heisenberg limit; if device noise is present, BAE can dynamically characterize it and ...
Alexandra Ramôa, Luis Paulo Santos
doaj   +1 more source

Bayesian Execution Skill Estimation

Proceedings of the AAAI Conference on Artificial Intelligence, 2019
The performance of agents in many domains with continuous action spaces depends not only on their ability to select good actions to execute, but also on their ability to execute planned actions precisely. This ability, which has been called an agent’s execution skill, is an important characteristic of an agent which can have a significant impact on ...
Christopher Archibald, Delma Nieves-Rivera   +1 more
openaire   +2 more sources