Autor: Beluch, Witold - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Multiobjective global optimization of mechanical systems with cracks
Autorzy:: Beluch, Witold
Dlugosz, Adam
Powiązania:: https://bibliotekanauki.pl/articles/1839645.pdf
Data publikacji:: 2020
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:: multiobjective optimization
crack
dual BEM
NURBS
Pareto front
Opis:: The paper is devoted to the multiobjective shape optimization of cracked structures. The two main goals are: reduction of the negative crack influence of identified cracks and optimal design of structural elements to reduce the risk of crack occurrence and growth. NURBS (Non-Uniform Rational B-Splines) curves are used to model the structure boundaries. Global optimization methods in the form of evolutionary algorithms are employed. As different optimization criteria are considered simultaneously, the efficient multiobjective optimization method are applied. An in-house multiobjective evolutionary algorithm is proposed as an efficient optimization tool. The dual boundary element method is used to solve the boundaryvalue problem.
Źródło:: Journal of Theoretical and Applied Mechanics; 2020, 58, 2; 553-564
1429-2955
Pojawia się w:: Journal of Theoretical and Applied Mechanics
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Convolutional neural networks in the detection of astronomical objects from the Messier catalog
Autorzy:: Beluch, Witold
Śliwa, Paweł
Powiązania:: https://bibliotekanauki.pl/articles/38703870.pdf
Data publikacji:: 2023
Wydawca:: Instytut Podstawowych Problemów Techniki PAN
Tematy:: convolutional neural networks
astronomical objects detection
Messier catalog
konwolucyjna sieć neuronowa
wykrywanie obiektów astronomicznych
katalog Messiera
Opis:: This paper explores the application of convolutional neural networks in the field of amateur astronomy. The authors have employed the available astronomical datasets to develop a detector for identifying astronomical objects from the Messier catalog. A concept framework for creating such a detector for astronomical objects using artificial intelligence tools in the form of a detector based on convolutional neural networks is presented. Augmentation and pre-processing procedures have been used to extend the feature distribution in the training set. Examples confirming the effectiveness of the proposed detector of astronomical objects are presented.
Źródło:: Computer Assisted Methods in Engineering and Science; 2023, 30, 4; 461-479
2299-3649
Pojawia się w:: Computer Assisted Methods in Engineering and Science
Dostawca treści:: Biblioteka Nauki

Artykuł

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