PL
 |
EN
Preferencje help
Polish version English version Język
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 6

Liczba wyników na stronie
first rewind previous Strona / 1 next fast forward last
Wyniki wyszukiwania
Wyszukiwano:
w słowach kluczowych:  ABC algorithm
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 1 next fast forward last
1
Content available Selection of the heat transfer coefficient using swarming algorithms
Gawrońska Elżbieta, Dyja Robert, Zych Maria, Domek Grzegorz
Acta Mechanica et Automatica
|
2022
|
Vol. 16, no. 4
325--339
EN
The article presents the use of swarming algorithms in selecting the heat transfer coefficient, taking into account the boundary condition of the IV types. Numerical calculations were made using the proprietary TalyFEM program and classic form of swarming algorithms. A function was also used for the calculations, which, during the calculation, determined the error of the approximate solution and was minimalised using a pair of individually employed algorithms, namely artificial bee colony (ABC) and ant colony optimisation (ACO). The tests were carried out to select the heat transfer coefficient from one range. Describing the geometry for a mesh of 408 fine elements with 214 nodes, the research carried out presents two squares (one on top of the other) separated by a heat transfer layer with a κ coefficient. A type III boundary condition was established on the right and left of both edges. The upper and lower edges were isolated, and a type IV boundary condition with imperfect contact was established between the squares. Calculations were made for ABC and ACO, respectively, for populations equal to 20, 40 and 60 individuals and 2, 6 and 12 iterations. In addition, in each case, 0%, 1%, 2% and 5% noise of the reference values were also considered. The obtained results are satisfactory and very close to the reference values of the κ parameter. The obtained results demonstrate the possibility of using artificial intelligence (AI) algorithms to reconstruct the IV type boundary condition value during heat conduction modelling.
2
Content available remote Estimation of recovery cost with TCSC in dynamic economic dispatch
Sekharan S., Balasubramanian K.
Przegląd Elektrotechniczny
|
2017
|
R. 93, nr 5
25--29
EN
In this paper, Dynamic Economic Dispatch (DED) problem incorporating TCSC is solved using ABC algorithm. The percentage of cost recovered with the installation if TCSC is estimated. Here dispatch is carried out for a time horizon of 24 hours by considering the ramp up/down constraints along with the prevailing constraints. The percentage gain obtained with TCSC is demonstrated with respected to Equated Monthly Instalment (EMI) paid on the installation cost. The proposed methodology is tested and validated on South Indian 86 bus utility and an IEEE 118 bus test system.
PL
W artykule rozwiązywany jest problem Ekonomicznego Rozsyłu Energii DED w układzie z tyrystorowo sterowanymi kompensatorami TCSC. Oceniany jest procentowy koszt instalacji TCSC a następnie koszt rozsyłu energii w ciągu 24 godzin przy schodkowych zmianach wymuszeń. System przetestowano w układzie IEEE 118 w Południowych Indiach.
3
Content available remote Artificial Bee Colony Algorithm for the Protein Structure Prediction Based on the Toy Model
Li Y., Zhou C., Zheng X.
Fundamenta Informaticae
|
2015
|
Vol. 136, nr 3
241--252
EN
The protein structure folding is one of the most challenging problems in the field of bioinformatics. The main problem of protein structure prediction in the 3D toy model is to find the lowest energy conformation. Although many heuristic algorithms have been proposed to solve the protein structure prediction (PSP) problem, the existing algorithms are far from perfect since PSP is an NP-problem. In this paper, we proposed an artificial bee colony (ABC) algorithm based on the toy model to solve PSP problem. In order to improve the global convergence ability and convergence speed of the ABC algorithm, we adopt a new search strategy by combining the global solution into the search equation. Experimental results illustrate that the suggested algorithm can get the lowest energy when the algorithm is applied to the Fibonacci sequences and to four real protein sequences which come from the Protein Data Bank (PDB). Compared with the results obtained by PSO, LPSO, PSO-TS, PGATS, our algorithm is more efficient.
4
Content available Optimal location of interline power flow controller in a power system network using ABC algorithm
Sreejith S., Psimon S., Selvan M.P.
Archives of Electrical Engineering
|
2013
|
Vol. 62, nr 1
91-110
EN
This paper proposes a methodology based on installation cost for locating the optimal position of interline power flow controller (IPFC) in a power system network. Here both conventional and non conventional optimization tools such as LR and ABC are applied. This methodology is formulated mathematically based on installation cost of the FACTS device and active power generation cost. The capability of IPFC to control the real and reactive power simultaneously in multiple transmission lines is exploited here. Apart from locating the optimal position of IPFC, this algorithm is used to find the optimal dispatch of the generating units and the optimal value of IPFC parameters. IPFC is modeled using Power Injection (PI) model and incorporated into the problem formulation. This proposed method is compared with that of conventional LR method by validating on standard test systems like 5-bus, IEEE 30-bus and IEEE 118-bus systems. A detailed discussion on power flow and voltage profile improvement is carried out which reveals that incorporating IPFC into power system network in its optimal location significantly enhance the load margin as well as the reliability of the system.
5
Content available remote Application of swarm intelligence algorithms in solving the inverse heat conduction problem
Hetmaniok E., Słota D., Zielonka A.
Computer Assisted Methods in Engineering and Science
|
2012
|
Vol. 19, no. 4
361-367
EN
In the paper a proposal of using selected swarm intelligence algorithms for solving the inverse heat conduction problem is presented. The analyzed problem consist s in reconstructing temperature distribution in the given domain and the form of heat transfer coefficient ap pearing in the boundary condition of the third kind. The investigated approaches are based on the Art ificial Bee Colony algorithm and the Ant Colony Optimization algorithm, the efficiency of which are ex amined and compared
6
Content available Identification of the Heat Transfer Coefficient in the Inverse Stefan Problem by Using the ABC Algorithm
Hetmaniok E., Słota D., Zielonka A.
Archives of Foundry Engineering
|
2012
|
Vol. 12, iss. 2s
27--32
EN
A procedure based on the Artificial Bee Colony algorithm for solving the two-phase axisymmetric one-dimensional inverse Stefan problem with the third kind boundary condition is presented in this paper. Solving of the considered problem consists in reconstruction of the function describing the heat transfer coefficient appearing in boundary condition of the third kind in such a way that the reconstructed values of temperature would be as closed as possible to the measurements of temperature given in selected points of the solid. A crucial part of the solution method consists in minimizing some functional which will be executed with the aid of one of the swarm intelligence algorithms - the ABC algorithm.
first rewind previous Strona / 1 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.