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Wyszukujesz frazę "genetic optimization algorithm" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Multi-variable optimization of an ytterbium-doped fiber laser using genetic algorithm
Autorzy:
Hashemi, S. S.
Ghavami, S. S.
Khorsandi, A
Powiązania:
https://bibliotekanauki.pl/articles/175086.pdf
Data publikacji:
2015
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
fiber laser
optimization
genetic algorithm
Opis:
We introduce the genetic algorithm for the optimization of an Yb3+-doped double-clad fiber laser based on a multi-variable scheme. The output characteristic of the laser is numerically simulated using real practical values. This is performed through solving the associated steady-state rate equation and investigating the effects of input variables such as pump and signal wavelengths and length of the fiber on the laser output. It is found that pumping of the medium around 975 nm is conducted to attain the maximum output power of ~34.8 W, while the stability of the outcoupled power is significantly improved when pumping at 920 nm, confirming good agreement with the reported experimental results. We have also found that by using genetic algorithm base multi-variable optimization, the output power can be significantly increased by about three orders of magnitude and reaches to ~28.5 W with optimum and shorter fiber length of ~57.5 m. Obtained results show that based on the genetic algorithm multi-variable discipline, fiber characteristics can be optimized according to the gaining of maximum output power.
Źródło:
Optica Applicata; 2015, 45, 3; 355-367
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simultaneous optimization of flotation column performance using genetic evolutionary algorithm
Autorzy:
Nakhaei, F.
Irannajad, M.
Yousefikhoshbakht, M.
Powiązania:
https://bibliotekanauki.pl/articles/110806.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
flotation column
optimization
genetic algorithm
non-linear regression
upgrading curve
Opis:
Column flotation is a multivariable process. Its optimization guarantees the metallurgical yield of the process, expressed by the grade and recovery of the concentrate. The present work aimed at applying genetic algorithms (GAs) to optimize a pilot column flotation process which is characterized by being difficult to be optimized via conventional methods. A non-linear mathematical model was used to describe the dynamic behavior of the multivariable process. The solution of the optimization problem using conventional algorithms does not always lead to convergence because of the high dimensionality and non-linearity of the model. In order to deal with this process, the use of a genetic evolutionary algorithm is justified. In this way, GA was coupled with the multivariate non-linear regression (MNLR) of the column flotation metallurgical performance as a fitting function in order to optimize the column flotation process. Then, this kind of intelligent approach was verified by using mineral processing approaches such as Halbich’s upgrading curve. The aim of the optimization through GAs was searching for the process inputs that maximize the productivity of copper in the Sarcheshmeh pilot plant. In this case, the simulation optimization problem was defined as finding the best values for the froth height, chemical reagent dosage, wash water, air flow rate, air holdup, and Cu grade in rougher and column feed streams. The results indicated that GA was a robust and powerful search method to find the best values of the flotation column model parameters that lead to more reliable simulation predictions at a reasonable time. Based on the grade–recovery Halbich upgrading curve, the MNLR model coupled with GA can be used for determination of the flotation optimum conditions.
Źródło:
Physicochemical Problems of Mineral Processing; 2016, 52, 2; 874-893
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Numerical analysis of tailing dam with calibration based on genetic algorithm and geotechnical monitoring data
Autorzy:
Grosel, Szczepan
Powiązania:
https://bibliotekanauki.pl/articles/1845160.pdf
Data publikacji:
2021
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
soil parameters
optimization
slope stability
genetic algorithm
observational method
monitoring
Opis:
The article presents a method of calibration of material parameters of a numerical model based on a genetic algorithm, which allows to match the calculation results with measurements from the geotechnical monitoring network. This method can be used for the maintenance of objects managed by the observation method, which requires continuous monitoring and design alterations. The correctness of the calibration method has been verified on the basis of artificially generated data in order to eliminate inaccuracies related to approximations resulting from the numerical model generation. Using the example of the tailing dam model the quality of prediction of the selected measurement points was verified. Moreover, changes of factor of safety values, which is an important indicator for designing this type of construction, were analyzed. It was decided to exploit the case of dam of reservoir, which is under continuous construction, that is dam height is increasing constantly, because in this situation the use of the observation method is relevant.
Źródło:
Studia Geotechnica et Mechanica; 2021, 43, 1; 34-47
0137-6365
2083-831X
Pojawia się w:
Studia Geotechnica et Mechanica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Numerical verification of two-component dental implant in the context of fatigue life for various load cases
Autorzy:
Szajek, K.
Wierszycki, M.
Powiązania:
https://bibliotekanauki.pl/articles/307214.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
implant stomatologiczny
optymalizacja
trwałość zmęczeniowa
algorytm genetyczny
dental implant
optimization
fatigue life
genetic algorithm
Opis:
Purpose: Dental implant designing is a complex process which considers many limitations both biological and mechanical in nature. In earlier studies, a complete procedure for improvement of two-component dental implant was proposed. However, the optimization tasks carried out required assumption on representative load case, which raised doubts on optimality for the other load cases. This paper deals with verification of the optimal design in context of fatigue life and its main goal is to answer the question if the assumed load scenario (solely horizontal occlusal load) leads to the design which is also “safe” for oblique occlussal loads regardless the angle from an implant axis. Methods: The verification is carried out with series of finite element analyses for wide spectrum of physiologically justified loads. The design of experiment methodology with full factorial technique is utilized. All computations are done in Abaqus suite. Results: The maximal Mises stress and normalized effective stress amplitude for various load cases are discussed and compared with the assumed “safe” limit (equivalent of fatigue life for 5e6 cycles). Conclusions: The obtained results proof that coronial-appical load component should be taken into consideration in the two component dental implant when fatigue life is optimized. However, its influence in the analyzed case is small and does not change the fact that the fatigue life improvement is observed for all components within whole range of analyzed loads.
Źródło:
Acta of Bioengineering and Biomechanics; 2016, 18, 1; 103-113
1509-409X
2450-6303
Pojawia się w:
Acta of Bioengineering and Biomechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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