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Wyszukujesz frazę "artificial bee colony" wg kryterium: Temat


Tytuł:
Comparison of data mining techniques to predict and map the Atterberg limits in central plateau of Iran
Autorzy:
Amin, Peyman
Taghizadeh-Mehrjardi, Ruhollah
Akbarzadeh, Ali
Shirmardi, Mostafa
Tematy:
Atterberg limits, artificial bee colony, artificial neural networks, support vector machine, regression tree
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Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Powiązania:
https://bibliotekanauki.pl/articles/762833.pdf  Link otwiera się w nowym oknie
Opis:
The Atterberg limits display soil mechanical behavior and, therefore, can be so important for topics related to soil management. The aim of the research was to investigate the spatial variability of the Atterberg limits using three most common digital soil-mapping techniques, the pool of easy-to-obtain environmental variables and 85 soil samples in central Iran. The results showed that the maximum amount of liquid limit (LL) and plastic limit (PL) were obtained in the central, eastern and southeastern parts of the study area where the soil textural classes were loam and clay loam. The minimum amount of LL and PL were related to the northwestern parts of the study area, adjacent to the mountain regions, where the samples had high levels of sand content (>80%). The ranges of plasticity index (PI) in the study area were obtained between 0.01 to 4%. According to the leave-in-out cross-validation method, it should be highlighted the combination of artifiial bee colony algorithm (ABC) and artifiial neural network (ANN) techniques were the best model to predict the Atterberg limits in the study area, compared to the support vector machine and regression tree model. For instance, ABC-ANN could predict PI with RMSE, R2 and ME of 0.23, 0.91 and -0.03, respectively. Our fiding generally indicated that the proposed method can explain the most of variations of the Atterberg limits in the study area, and it could berecommended, therefore, as an indirect approach to assess soil mechanical properties in the arid regions, where the soil survey/sampling is difficult to undertake.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficiency analysis of parallel computing applied to auto-tuning of state feedback speed controller for PMSM drive
Autorzy:
Szczepański, Rafał
Tarczewski, Tomasz
Grzesiak, Lech M.
Tematy:
parallel computing
Artificial Bee Colony
PMSM
state feedback
controller
MATLAB/Simulink
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Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Powiązania:
https://bibliotekanauki.pl/articles/376463.pdf  Link otwiera się w nowym oknie
Opis:
Nowadays the simulation is inseparable part of researcher's work. Its computation time may significantly exceed the experiment time. On the other hand, multi-core processors are common in personal computers. These processors can be used to reduce computation time by using parallel computing on multiple cores. The most popular software applied to simulate behavior of the plant is MATLAB/Simulink. A single simulation of Simulink model cannot be computed by multiple cores, but there are many engineering problems, that require a multiple simulation of the same model with different parameters. In these problems, the parallel computing can be employed to decrease the overall simulation time. In this paper the parallel computing is used to speed-up the auto-tuning process of state feedback speed controller for PMSM drive. In order to obtain the optimal coefficients of the controller, an Artificial Bee Colony optimization algorithm is employed.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
ABC-CAG: Covering Array Generator for Pair-wise Testing Using Artificial Bee Colony Algorithm
Autorzy:
Bansal, P.
Sabharwal, S.
Mittal, N.
Arora, S.
Tematy:
combinatorial interaction testing
pair-wise testing
covering array
artificial bee colony
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/384141.pdf  Link otwiera się w nowym oknie
Opis:
Testing is an indispensable part of the software development life cycle. It is performed to improve the performance, quality and reliability of the software. Various types of testing such as functional testing and structural testing are performed on software to uncover the faults caused by an incorrect code, interaction of input parameters, etc. One of the major factors in deciding the quality of testing is the design of relevant test cases which is crucial for the success of testing. In this paper we concentrate on generating test cases to uncover faults caused by the interaction of input parameters. It is advisable to perform thorough testing but the number of test cases grows exponentially with the increase in the number of input parameters, which makes exhaustive testing of interaction of input parameters imprudent. An alternative to exhaustive testing is combinatorial interaction testing (CIT) which requires that every t-way interaction of input parameters be covered by at least one test case. Here, we present a novel strategy ABC-CAG (Artificial Bee Colony-Covering Array Generator) based on the Artificial Bee Colony (ABC) algorithm to generate covering an array and a mixed covering array for pair-wise testing. The proposed ABC-CAG strategy is implemented in a tool and experiments are conducted on various benchmark problems to evaluate the efficacy of the proposed approach. Experimental results show that ABC-CAG generates better/comparable results as compared to the existing state-of-the-art algorithms.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of artificial bee colony algorithm to auto-tuning of state feedback controller for DC-DC power converter
Autorzy:
Tarczewski, T.
Niewiara, Ł. J.
Grzesiak, L M.
Tematy:
artificial bee colony algorithm
state feedback controller
DC-DC power converter
SiC MOSFET
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/1193254.pdf  Link otwiera się w nowym oknie
Opis:
The article presents an auto-tuning method of state feedback voltage controller for DC-DC power converter. The penalty matrices employed for calculation of controller’s coefficients were obtained by using nature-inspired artificial bee colony (ABC) optimization algorithm. This overcomes the main drawback of state feedback control related to time-consuming trial-and-error tuning procedure. The optimization algorithm takes into account constraints of selected state and control variables of DC-DC power converter. In order to meet all control objectives (i.e., fast voltage response and chattering-free control signal) an appropriate performance index is proposed. Proper selection of state feedback controller (SFC) coefficients is proven by simulation and experimental tests of DC-DC power converter.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Condition assessment of transformer insulation using dielectric frequency response analysis by artificial bee colony algorithm
Autorzy:
Bigdeli, M.
Aghajanloo, J.
Tematy:
artificial bee colony (ABC) algorithm
condition assessment
dielectric frequency
response (DFR)
transformer insulation
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Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/140546.pdf  Link otwiera się w nowym oknie
Opis:
Transformers are one of the most important components of the power system. It is important to maintain and assess the condition. Transformer lifetime depends on the life of its insulation and insulation life is also strongly influenced by moisture in the insulation. Due to importance of this issue, in this paper a new method is introduced for determining the moisture content of the transformer insulation system using dielectric response analysis in the frequency domain based on artificial bee colony algorithm. First, the master curve of dielectric response is modeled. Then, using proposed method the master curve and the measured dielectric response curves are compared. By analyzing the results of the comparison, the moisture content of paper insulation, electrical conductivity of the insulating oil and dielectric model dimensions are determined. Finally, the proposed method is applied to several practical samples to demonstrate its capabilities compared with the well-known conventional method.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Particle swarm optimization and discrete artificial bee colony algorithms for solving production scheduling problems
Autorzy:
Witkowski, Tadeusz
Tematy:
Discrete Artificial Bee Colony
particle swarm optimization (PSO)
production scheduling problem
makespan
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Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Powiązania:
https://bibliotekanauki.pl/articles/298169.pdf  Link otwiera się w nowym oknie
Opis:
This paper shows the use of Discrete Artificial Bee Colony (DABC) and Particle Swarm Optimization (PSO) algorithm for solving the job shop scheduling problem (JSSP) with the objective of minimizing makespan. The Job Shop Scheduling Problem is one of the most difficult problems, as it is classified as an NP-complete one. Stochastic search techniques such as swarm and evolutionary algorithms are used to find a good solution. Our objective is to evaluate the efficiency of DABC and PSO swarm algorithms on many tests of JSSP problems. DABC and PSO algorithms have been developed for solving real production scheduling problem too. The experiment results indicate that this problem can be effectively solved by PSO and DABC algorithms.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting Stock Price using Wavelet Neural Network Optimized by Directed Artificial Bee Colony Algorithm
Autorzy:
Khuat, T. T.
Le, Q. C.
Nguyen, B. L.
Le, M. H.
Tematy:
Artificial Bee Colony algorithm
Artificial Neural Network
back-propagation algorithm
stock price forecasting
wavelet transform
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Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/308651.pdf  Link otwiera się w nowym oknie
Opis:
Stock prediction with data mining techniques is one of the most important issues in finance. This field has attracted great scientific interest and has become a crucial research area to provide a more precise prediction process. This study proposes an integrated approach where Haar wavelet transform and Artificial Neural Network optimized by Directed Artificial Bee Colony algorithm are combined for the stock price prediction. The proposed approach was tested on the historical price data collected from Yahoo Finance with different companies. Furthermore, the prediction result was found satisfactorily enough as a guide for traders and investors in making qualitative decisions.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial bee colony based state feedback position controller for PMSM servo-drive – the efficiency analysis
Autorzy:
Tarczewski, T.
Niewiara, L. J.
Grzesiak, L. M.
Tematy:
tuning
PMSM servo-drive
artificial bee colony algorithm
linear-quadratic optimization problem
pole placement
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Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/200239.pdf  Link otwiera się w nowym oknie
Opis:
This paper presents a state feedback controller (SFC) for position control of PMSM servo-drive. Firstly, a short review of the commonly used swarm-based optimization algorithms for tuning of SFC is presented. Then designing process of current control loop as well as of SFC with feedforward path is depicted. Next, coefficients of controller are tuned by using an artificial bee colony (ABC) optimization algorithm. Three of the most commonly applied tuning methods (i.e. linear-quadratic optimization, pole placement technique and direct selection of coefficients) are used and investigated in terms of positioning performance, disturbance compensation and robustness against plant parameter changes. Simulation analysis is supported by experimental tests conducted on laboratory stand with modern PMSM servo-drive.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-AUV distributed task allocation based on the differential evolution quantum bee colony optimization algorithm
Autorzy:
Li, J.
Zhang, R.
Tematy:
differential evolution quantum artificial bee colony algorithm
multi-AUV
contract net
task allocation
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Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Powiązania:
https://bibliotekanauki.pl/articles/259994.pdf  Link otwiera się w nowym oknie
Opis:
The multi-autonomous underwater vehicle (AUV) distributed task allocation model of a contract net, which introduces an equilibrium coefficient, has been established to solve the multi-AUV distributed task allocation problem. A differential evolution quantum artificial bee colony (DEQABC) optimization algorithm is proposed to solve the multi-AUV optimal task allocation scheme. The algorithm is based on the quantum artificial bee colony algorithm, and it takes advantage of the characteristics of the differential evolution algorithm. This algorithm can remember the individual optimal solution in the population evolution and internal information sharing in groups and obtain the optimal solution through competition and cooperation among individuals in a population. Finally, a simulation experiment was performed to evaluate the distributed task allocation performance of the differential evolution quantum bee colony optimization algorithm. The simulation results demonstrate that the DEQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The DEQABC algorithm can effectively improve AUV distributed multi-tasking performance.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On the hybridization of the artificial Bee Colony and Particle Swarm Optimization Algorithms
Autorzy:
El-Abd, M.
Tematy:
Artificial Bee Colony Algorithm
ABC
particle swarm optimization (PSO)
PSO
hybridization
hybrid algorithm
CEC05
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Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Powiązania:
https://bibliotekanauki.pl/articles/91658.pdf  Link otwiera się w nowym oknie
Opis:
In this paper we investigate the hybridization of two swarm intelligence algorithms; namely, the Artificial Bee Colony Algorithm (ABC) and Particle Swarm Optimization (PSO). The hybridization technique is a component-based one, where the PSO algorithm is augmented with an ABC component to improve the personal bests of the particles. Three different versions of the hybrid algorithm are tested in this work by experimenting with different selection mechanisms for the ABC component. All the algorithms are applied to the well-known CEC05 benchmark functions and compared based on three different metrics, namely, the solution reached, the success rate, and the performance rate.
Dostawca treści:
Biblioteka Nauki
Artykuł

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