Results 41 to 50 of about 11,939,645 (246)

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

PENGGUNAAN SIMULASI MONTE CARLO DALAM ESTIMASI VALUE AT RISK (VaR) PORTOFOLIO YANG DIBENTUK DARI INDEKS HARGA SAHAM MULTINASIONAL

E-Jurnal Matematika, 2022
Investment is buying an asset that is expected in the future can be resold and get a high profit value. There are two factors that must be considered when you want to invest in stocks, namely the rate of return on stocks and risk factors.
NABILA NUR JANNAH, KOMANG DHARMAWAN, LUH PUTU IDA HARINI   +2 more
doaj   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

An Efficient Anti-Optimization Approach for Uncertainty Analysis in Composite Laminates

Materials Research, 2021
This work presents an efficient approach to quantify uncertainties in composite laminates using the interval analysis, anti-optimization technique, and the α-cut procedure.
Pedro Bührer Santana, Ewerton Grotti, Herbert Martins Gomes   +2 more
doaj   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement

The Scientific World Journal, 2014
Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction.
Joko Siswantoro, Anton Satria Prabuwono, Azizi Abdullah, Bahari Idrus   +3 more
doaj   +1 more source

A comparative study between Classical Numerical Methods and Monte Carlo Methods [PDF]

المجلة العراقية للعلوم الاحصائية, 2008
Recently, there is a great interest in the methods of Monte Carlo used for the treatment of different technical and scientific issues. This research deals with using the Monte Carlo methods in numerical integration by making a general comparison between
doaj   +1 more source

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

A top-down iteration algorithm for Monte Carlo method for probability estimation of a fault tree with circular logic

Nuclear Engineering and Technology, 2018
Calculating minimal cut sets is a typical quantification method used to evaluate the top event probability for a fault tree. If minimal cut sets cannot be calculated or if the accuracy of the quantification result is in doubt, the Monte Carlo method can ...
Sang Hoon Han
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source