Results 71 to 80 of about 5,790,115 (297)

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Recursive Markov Decision Processes and Recursive Stochastic Games [PDF]

, 2005
We introduce Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs), and study the decidability and complexity of algorithms for their analysis and verification.
Mihalis Yannakakis, Yannakakis, Mihalis, Etessami, Kousha; id_orcid, Kousha Etessami   +3 more
core   +1 more source

Stochastic Process Algebras [PDF]

, 2007
In this tutorial we give an introduction to stochastic process algebras and their use in performance modelling, with a focus on the PEPA formalism. A brief introduction is given to the motivations for extending classical process algebra with stochastic times and probabilistic choice.
Clark, Allan, Gilmore, Stephen, Hillston, Jane, Tribastone, Mirco   +3 more
openaire   +3 more sources

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

Estimation of the Inverse Power Lindley Distribution Parameters Using Ranked Set Sampling with an Application to Failure Time Data

Axioms
In this paper, the ranked set sampling method (RSS) is considered for estimating the inverse power Lindley distribution (IPLD) parameters and compared with the commonly simple random sampling.
Ghadah Alomani, Sid Ahmed Benchiha, Amer Ibrahim Al-Omari   +2 more
doaj   +1 more source

Introducing Plithogenic Stochastic Processes with an Application to Poisson Process [PDF]

Neutrosophic Sets and Systems
In this paper, we study and define the mathematical form of plithogenic stochastic processes PSP based on set of three classic stochastic processes. This new definition is a generalization of neutrosophic stochastic process.
Abdulrahman Astambli, Mohamed Bisher Zeina , Moustafa Mazhar Ranneh   +2 more
doaj   +1 more source

Quantum Stochastic Processes [PDF]

, 1985
Let ℬ be *-algebra with identity (usually it wil be a C*- or a W*-algebra). A quantum stochastic process over ℬ indexed by ℝ is defined by a triple {A, (jt)t∈ℝ, φ} where A is a *-algebra with identity. jt : ℬ ↪A is an embedding (t∈ℝ). φ is a State on A.
openaire   +2 more sources

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

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Enhanced Estimation of the Unit Lindley Distribution Parameter via Ranked Set Sampling with Real-Data Application

Mathematics
This paper investigates various estimation methods for the parameters of the unit Lindley distribution (U-LD) under both ranked set sampling (RSS) and simple random sampling (SRS) designs.
Sid Ahmed Benchiha, Amer Ibrahim Al-Omari, Ghadah Alomani   +2 more
doaj   +1 more source