Results 51 to 60 of about 1,147,771 (298)

Stochastic modelling [PDF]

Proceedings of the workshop on Data-driven methods in machine translation -, 2001
This paper gives an overview of the stochastic modelling approach to machine translation. Starting with the Bayes decision rule as in pattern classification and speech recognition, we show how the resulting system architecture can be structured into three parts: the language model probability, the string translation model probability and the search ...
openaire   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Stochastic Models of Exotic Transport

, 2000
Non-typical transport phenomena may arise when randomly driven particles remain in an active relationship with the environment instead of being passive. If we attribute to Brownian particles an ability to induce alterations of the environment on suitable
Garbaczewski, Piotr
core   +1 more source

Adiabatic elimination in quantum stochastic models [PDF]

, 2007
We consider a physical system with a coupling to bosonic reservoirs via a quantum stochastic differential equation. We study the limit of this model as the coupling strength tends to infinity.
A.C. Doherty, Andrew Silberfarb, C. Cohen-Tannoudji, C.W. Gardiner, C.W. Gardiner, D.F. Walls, E.B. Davies, E.B. Davies, G.C. Papanicolaou, H. Trotter, H.M. Wiseman, I.H. Deutsch, J. Derezinski, J. Gough, J. Gough, J.A. Dunningham, K.S. Wong, L. Accardi, L.-M. Duan, Luc Bouten, R.L. Hudson, T. Kato, T.G. Kurtz, T.G. Kurtz   +23 more
core   +2 more sources

Functional Conditional Volatility Modeling With Missing Data: Inference and Application to Energy Commodities

Journal of Mathematics
This paper explores the nonparametric estimation of the volatility component in a heteroscedastic scalar-on-function regression model, where the underlying discrete-time process is ergodic and subject to a missing-at-random mechanism.
Abdelbasset Djeniah, Mohamed Chaouch, Amina Angelika Bouchentouf   +2 more
doaj   +1 more source

Modeling and optimizing an AMS with DV policy, waiting servers, impatient customers, and failures: A queueing analysis

Results in Control and Optimization
In this paper, we analyze an automated manufacturing system modeled as a queueing system with multiple servers, differentiated vacation (DV) policy, customer impatience, and server failures.
Amina Angelika Bouchentouf, Lahcene Yahiaoui, Ines Ziad   +2 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Analysis of a Class of Stochastic Animal Behavior Models under Specific Choice Preferences

Mathematics, 2022
The behavior of animals can be studied in two ways: experimentally, in labs or in the field, or theoretically, via modeling. Extensive research on animal behavior in probabilistic learning circumstances has produced findings that are consistent with so ...
Ali Turab, Nabil Mlaiki, Nahid Fatima, Zoran D. Mitrović, Wajahat Ali   +4 more
doaj   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Stochastic models of the chemostat [PDF]

, 2010
We consider the modeling of the dynamics of the chemostat at its very source. The chemostat is classically represented as a system of ordinary differential equations.
Campillo, Fabien, Joannides, Marc, Larramendy, Irène   +2 more
core   +3 more sources