Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Martin Holena"'
Publikováno v:
Crystals, Vol 13, Iss 12, p 1659 (2023)
In this study, an axisymmetric Czochralski furnace model for the LEC growth of gallium arsenide is presented. We produced 88 datasets through computational fluid dynamics simulations. Among the many parameters that affect crystal growth, a total of 1
Externí odkaz:
https://doaj.org/article/2ec1edbe1b174d22914def49a25a215f
Publikováno v:
Journal of Statistical Software, Vol 93, Iss 1, Pp 1-36 (2020)
To extend the current implementation of copulas in MATLAB to non-elliptical distributions in arbitrary dimensions enabling for asymmetries in the tails, the toolbox HACopula provides functionality for modeling with hierarchical (or nested) Archimedea
Externí odkaz:
https://doaj.org/article/87ca20f09e374c84965875ed47f1d260
Publikováno v:
Crystals, Vol 12, Iss 12, p 1764 (2022)
The aim of this study was to evaluate the potential of the machine learning technique of decision trees to understand the relationships among furnace design, process parameters, crystal quality, and yield in the case of the Czochralski growth of germ
Externí odkaz:
https://doaj.org/article/b8df9107bdce4376bc618f5ebd39f774
Publikováno v:
Crystals, Vol 11, Iss 10, p 1218 (2021)
The aim of this study was to assess the ability of the various data mining and supervised machine learning techniques: correlation analysis, k-means clustering, principal component analysis and decision trees (regression and classification), to deriv
Externí odkaz:
https://doaj.org/article/b10f9fae32f142a284c653ac29bfb0fc
Publikováno v:
Crystals, Vol 11, Iss 2, p 138 (2021)
The aim of this study was to assess the aptitude of the recurrent Long Short-Term Memory (LSTM) neural networks for fast and accurate predictions of process dynamics in vertical-gradient-freeze growth of gallium arsenide crystals (VGF-GaAs) using dat
Externí odkaz:
https://doaj.org/article/000bf34d29da4bdf9fe9da1b8eb643d6
Autor:
Natasha Dropka, Martin Holena
Publikováno v:
Crystals, Vol 10, Iss 8, p 663 (2020)
In this review, we summarize the results concerning the application of artificial neural networks (ANNs) in the crystal growth of electronic and opto-electronic materials. The main reason for using ANNs is to detect the patterns and relationships in
Externí odkaz:
https://doaj.org/article/40f875a7dc5647418d879ed30dcafd1d
This book explores internet applications in which a crucial role is played by classification, such as spam filtering, recommender systems, malware detection, intrusion detection and sentiment analysis. It explains how such classification problems can
Autor:
Manfred Baerns, Martin Holena
The book provides a comprehensive treatment of combinatorial development of heterogeneous catalysts. In particular, two computer-aided approaches that have played a key role in combinatorial catalysis and high-throughput experimentation during the la
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27ba66c71e7e090759e33c5add77f78e
https://doi.org/10.1109/ijcnn55064.2022.9892510
https://doi.org/10.1109/ijcnn55064.2022.9892510
Publikováno v:
Crystals
Volume 11
Issue 10
Crystals, Vol 11, Iss 1218, p 1218 (2021)
Volume 11
Issue 10
Crystals, Vol 11, Iss 1218, p 1218 (2021)
The aim of this study was to assess the ability of the various data mining and supervised machine learning techniques: correlation analysis, k-means clustering, principal component analysis and decision trees (regression and classification), to deriv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e14a2e47d1d33b26007d3564fc6d4bb6