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Wyszukujesz frazę "firefly algorithm" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Investigations on the effects of nitrogen gas in CNC machining of SS304 using Taguchi and Firefly Algorithm
Autorzy:
Prasanth, P.
Sekar, T.
Sivapragash, M.
Powiązania:
https://bibliotekanauki.pl/articles/2090705.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
SS304 alloy
turning
Taguchi method
optimization
Firefly Algorithm
stop SS304
skręt
metoda Taguchi
optymalizacja
algorytm Firefly
Opis:
This work attempts to use nitrogen gas as a shielding gas at the cutting zone, as well as for cooling purposes while machining stainless steel 304 (SS304) grade by Computer Numerical Control (CNC) lathe. The major influencing parameters of speed, feed and depth of cut were selected for experimentation with three levels each. Totally 27 experiments were conducted for dry cutting and N2 gaseous conditions. The major influencing parameters are optimized using Taguchi and Firefly Algorithm (FA). The improvement in obtaining better surface roughness and Material Removal Rate (MRR) is significant and the confirmation results revealed that the deviation of the experimental results from the empirical model is found to be within 5%. A significant improvement of reduction of the specific cutting energy by 2.57% on average was achieved due to the reduction of friction at the cutting zone by nitrogen gas in CNC turning of SS 304 alloy.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 1; e136211, 1--8
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Investigations on the effects of nitrogen gas in CNC machining of SS304 using Taguchi and Firefly Algorithm
Autorzy:
Prasanth, P.
Sekar, T.
Sivapragash, M.
Powiązania:
https://bibliotekanauki.pl/articles/2173582.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
SS304 alloy
turning
Taguchi method
optimization
Firefly Algorithm
stop SS304
skręt
metoda Taguchi
optymalizacja
algorytm Firefly
Opis:
This work attempts to use nitrogen gas as a shielding gas at the cutting zone, as well as for cooling purposes while machining stainless steel 304 (SS304) grade by Computer Numerical Control (CNC) lathe. The major influencing parameters of speed, feed and depth of cut were selected for experimentation with three levels each. Totally 27 experiments were conducted for dry cutting and N2 gaseous conditions. The major influencing parameters are optimized using Taguchi and Firefly Algorithm (FA). The improvement in obtaining better surface roughness and Material Removal Rate (MRR) is significant and the confirmation results revealed that the deviation of the experimental results from the empirical model is found to be within 5%. A significant improvement of reduction of the specific cutting energy by 2.57% on average was achieved due to the reduction of friction at the cutting zone by nitrogen gas in CNC turning of SS 304 alloy.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 1; art. no. e136211
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A parametric testing of the firefly algorithm in the determination of the optimal osmotic drying parameters of mushrooms
Autorzy:
Yeomans, J.S.
Powiązania:
https://bibliotekanauki.pl/articles/91745.pdf
Data publikacji:
2014
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
Firefly Algorithm
FA
osmotic dehydration
mushroom
dehydration model
surface technique
mathematical programming
optimal process parameters
Opis:
The Firefly Algorithm (FA) is employed to determine the optimal parameter settings in a case study of the osmotic dehydration process of mushrooms. In the case, the functional form of the dehydration model is established through a response surface technique and the resulting mathematical programming is formulated as a non-linear goal programming model. For optimization purposes, a computationally efficient, FA-driven method is used and the resulting optimal process parameters are shown to be superior to those from previous approaches. The final section of this study provides a computational experimentation performed on the FA to analyze its relative sensitivity over a range of the two key parameters that most influence its running time.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 4; 257-256
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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