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    Wyświetlanie 1-13 z 13
    Tytuł:
    Algorytmy stadne w problemach optymalizacji
    Swarm Algorithms in Optimization Problems
    Autorzy:
    Filipowicz, B.
    Kwiecień, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/274567.pdf
    Data publikacji:
    2011
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    optymalizacja nieliniowa
    algorytm PSO
    algorytm pszczeli
    algorytm świetlika
    nonlinear optimization
    particle swarm optimization (PSO)
    bee algorithm
    firefly algorithm
    Opis:
    W artykule przedstawiono zastosowanie algorytmu optymalizacji rojem cząstek, algorytmu pszczelego i algorytmu świetlika do wyznaczenia optymalnego rozwiązania wybranych testowych funkcji ciągłych. Przedstawiono i porównano wyniki badań dla funkcji Rosenbrocka, Rastrigina i de Jonga.
    This paper presents particle swarm optimization, bee algorithm and firefly algorithm, used for optimal solution of selected continuous well-known functions. Results of these algorithms are compared to each other on Rosenbrock, Rastrigin and de Jong functions.
    Źródło:
    Pomiary Automatyka Robotyka; 2011, 15, 12; 152-157
    1427-9126
    Pojawia się w:
    Pomiary Automatyka Robotyka
    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.
    Powiązania:
    https://bibliotekanauki.pl/articles/308651.pdf
    Data publikacji:
    2016
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    Artificial Bee Colony algorithm
    Artificial Neural Network
    back-propagation algorithm
    stock price forecasting
    wavelet transform
    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.
    Źródło:
    Journal of Telecommunications and Information Technology; 2016, 2; 43-52
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the hybridization of the artificial Bee Colony and Particle Swarm Optimization Algorithms
    Autorzy:
    El-Abd, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/91658.pdf
    Data publikacji:
    2012
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    Artificial Bee Colony Algorithm
    ABC
    particle swarm optimization (PSO)
    PSO
    hybridization
    hybrid algorithm
    CEC05
    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.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 2; 147-155
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    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.
    Powiązania:
    https://bibliotekanauki.pl/articles/1193254.pdf
    Data publikacji:
    2016
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    artificial bee colony algorithm
    state feedback controller
    DC-DC power converter
    SiC MOSFET
    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.
    Źródło:
    Power Electronics and Drives; 2016, 1, 36/2; 83-96
    2451-0262
    2543-4292
    Pojawia się w:
    Power Electronics and Drives
    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.
    Powiązania:
    https://bibliotekanauki.pl/articles/259994.pdf
    Data publikacji:
    2017
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    differential evolution quantum artificial bee colony algorithm
    multi-AUV
    contract net
    task allocation
    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.
    Źródło:
    Polish Maritime Research; 2017, S 3; 65-71
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    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.
    Powiązania:
    https://bibliotekanauki.pl/articles/200239.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    tuning
    PMSM servo-drive
    artificial bee colony algorithm
    linear-quadratic optimization problem
    pole placement
    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.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 5; 997-1007
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multi-Objective Optimization of Traffic Signal Timing Using Non-Dominated Sorting Artificial Bee Colony Algorithm for Unsaturated Intersections
    Autorzy:
    Zhao, H.
    He, R.
    Su, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/223879.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    unsaturated intersection
    multi-objective optimization
    signal timing
    artificial bee colony algorithm
    vehicle delay
    vehicle stops
    Opis:
    Vehicle delay and stops at intersections are considered targets for optimizing signal timing for an isolated intersection to overcome the limitations of the linear combination and single objective optimization method. A multi-objective optimization model of a fixed-time signal control parameter of unsaturated intersections is proposed under the constraint of the saturation level of approach and signal time range. The signal cycle and green time length of each phase were considered decision variables, and a non-dominated sorting artificial bee colony (ABC) algorithm was used to solve the multi-objective optimization model. A typical intersection in Lanzhou City was used for the case study. Experimental results showed that a single-objective optimization method degrades other objectives when the optimized objective reaches an optimal value. Moreover, a reasonable balance of vehicle delay and stops must be achieved to flexibly adjust the signal cycle in a reasonable range. The convergence is better in the non-dominated sorting ABC algorithm than in non-dominated sorting genetic algorithm II, Webster timing, and weighted combination methods. The proposed algorithm can solve the Pareto front of a multi-objective problem, thereby improving the vehicle delay and stops simultaneously.
    Źródło:
    Archives of Transport; 2018, 46, 2; 85-96
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Comparison of different approaches in traffic forecasting models for the D-200 highway in Turkey
    Autorzy:
    Dogan, E.
    Korkmaz, E.
    Akgungor, A. P.
    Powiązania:
    https://bibliotekanauki.pl/articles/196318.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
    Tematy:
    traffic forecasting
    SARIMA
    differential evolution algorithm
    artificial bee colony algorithm
    prognozowanie ruchu
    algorytm ewolucji różnicowej
    algorytm sztucznej kolonii pszczół
    Opis:
    Short-term traffic estimations have a significant influence in terms of effectively controlling vehicle traffic. In this study, short-term traffic forecasting models have been developed based on different approaches. Seasonal autoregressive integrated moving average (SARIMA), artificial bee colony (ABC) and differential evolution (DE) algorithms are the techniques used in the optimization of models, which have been developed by using observation data for the D-200 highway in Turkey. 80% of the data were used for training, with the remaining data used for testing. The performances of the models were illustrated with mean absolute errors (MAEs), mean absolute percentage errors (MAPEs), the coefficient of determination (R2) and the root-mean-square errors (RMSEs). It is understood that all the models provided consistent and useful results when the developed models were compared with the statistical results. In the models created separately for two lanes, the R2 values of the models were calculated to be approximately 92% for the right lane, which is generally used by heavy vehicles, and 88% for the left lane, which is used by less traffic. Based on the MAE and RMSE values, the model developed by the ABC algorithm gave the lowest error and showed more effective performance than the other approaches. Thus, the ABC model showed that it is appropriate for use on other highways in Turkey.
    Źródło:
    Zeszyty Naukowe. Transport / Politechnika Śląska; 2018, 99; 25-42
    0209-3324
    2450-1549
    Pojawia się w:
    Zeszyty Naukowe. Transport / Politechnika Śląska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The prioritisation of production orders under the bee colony algorithm
    Szeregowanie zleceń produkcyjnych z zastosowaniem algorytmu pszczelego
    Autorzy:
    Jardzioch, A.
    Bulwan, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/176112.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    job shop scheduling
    artificial bee colony algorithm
    manufacturing system
    szeregowanie zleceń produkcyjnych
    algorytm pszczeli
    system wytwarzania
    Opis:
    The paper presents the problem of determining the prioritisation of production orders. The proposed criterion function allows a comprehensive evaluation of various ways of prioritising taking into account both the income derived from the execution of production orders and the penalty for any delays which may occur. The criterion function was implemented in an algorithm based on the operation of a colony of bees. The experiments which have been carried out make it possible to evaluate the solutions obtained through the provided algorithm and compare them with the solutions obtained through the typical heuristic rules. The results show that the prioritisation obtained through the algorithm is characterized by the highest qualities of the criterion function and is definitely superior to that obtained through the simple heuristic rules.
    W pracy przedstawiono zagadnienia ustalania kolejności wprowadzania zleceń do produkcji. Zaproponowano zastosowanie kompleksowej funkcji kryterialnej do oceny różnorodnych uszeregowań. Funkcja ta uwzględnia zarówno przychód uzyskany z realizacji zleceń produkcyjnych, jak i ewentualne kary za opóźnienia w ich wykonaniu. Opracowano algorytm oparty na działaniu roju pszczół, w którym zaimplantowano proponowaną funkcję kryterialną. Wykonane eksperymenty pozwoliły na ocenę uszeregowań uzyskiwanych z użyciem algorytmu pszczelego oraz ich porównanie z rozwiązaniami dla typowych reguł heurystycznych. Analiza otrzymanych wyników pozwoliła na stwierdzenie, że uszeregowania uzyskiwane z zastosowaniem opracowanego algorytmu cechowały się największymi wartościami funkcji kryterialnej. Zdecydowanie przewyższały uszeregowania uzyskiwane z wykorzystaniem prostych reguł heurystycznych.
    Źródło:
    Advances in Manufacturing Science and Technology; 2013, 37, 4; 49-59
    0137-4478
    Pojawia się w:
    Advances in Manufacturing Science and Technology
    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.
    Powiązania:
    https://bibliotekanauki.pl/articles/140546.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony (ABC) algorithm
    condition assessment
    dielectric frequency
    response (DFR)
    transformer insulation
    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.
    Źródło:
    Archives of Electrical Engineering; 2016, 65, 1; 45-57
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Online parameter identification of SPMSM based on improved artificial bee colony algorithm
    Autorzy:
    Wu, Chunli
    Jiang, Shuai
    Bian, Chunyuan
    Powiązania:
    https://bibliotekanauki.pl/articles/1955171.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony algorithm
    Euclidean distance
    online identification
    parameter identification
    urface-mounted permanent magnet synchronous motor
    algorytm sztucznej kolonii pszczół
    odległość euklidesowa
    identyfikacja online
    identyfikacja parametrów
    silnik synchroniczny z magnesami trwałymi montowany na powierzchni czołowej
    Opis:
    The artificial bee colony (ABC) intelligence algorithm is widely applied to solve multi-variable function optimization problems. In order to accurately identify the parameters of the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes an improved ABC optimization method based on vector control to solve the multi-parameter identification problem of the PMSM. Because of the shortcomings of the existing parameter identification algorithms, such as high computational complexity and data saturation, the ABC algorithm is applied for the multi-parameter identification of the PMSM for the first time. In order to further improve the search speed of the ABC algorithm and avoid falling into the local optimum, Euclidean distance is introduced into the ABC algorithm to search more efficiently in the feasible region. Applying the improved algorithm to multi-parameter identification of the PMSM, this method only needs to sample the stator current and voltage signals of the motor. Combined with the fitness function, the online identification of the PMSM can be achieved. The simulation and experimental results show that the ABC algorithm can quickly identify the motor stator resistance, inductance and flux linkage. In addition, the ABC algorithm improved by Euclidean distance has faster convergence speed and smaller steady-state error for the identification results of stator resistance, inductance and flux linkage.
    Źródło:
    Archives of Electrical Engineering; 2021, 70, 4; 777-790
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Nonlinear PID controller parameter optimization using modified hybrid artificial bee colony algorithm for continuous stirred tank reactor
    Autorzy:
    Pugazhenthi, Nedumal
    Selvaperumal, S.
    Vijayakumar, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/2128163.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony
    stirred tank reactor
    genetic algorithm
    nonlinear PID
    controller performance measures
    sztuczna kolonia pszczół
    reaktor zbiornikowy z mieszadłem
    algorytm genetyczny
    PID nieliniowy
    miernik wydajności kontrolera
    Opis:
    The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137348, 1--10
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Nonlinear PID controller parameter optimization using modified hybrid artificial bee colony algorithm for continuous stirred tank reactor
    Autorzy:
    Pugazhenthi, Nedumal
    Selvaperumal, S.
    Vijayakumar, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/2173628.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial bee colony
    stirred tank reactor
    genetic algorithm
    nonlinear PID
    controller performance measures
    sztuczna kolonia pszczół
    reaktor zbiornikowy z mieszadłem
    algorytm genetyczny
    PID nieliniowy
    miernik wydajności kontrolera
    Opis:
    The artificial bee colony (ABC) algorithm is well known and widely used optimization method based on swarm intelligence, and it is inspired by the behavior of honeybees searching for a high amount of nectar from the flower. However, this algorithm has not been exploited sufficiently. This research paper proposes a novel method to analyze the exploration and exploitation of ABC. In ABC, the scout bee searches for a source of random food for exploitation. Along with random search, the scout bee is guided by a modified genetic algorithm approach to locate a food source with a high nectar value. The proposed algorithm is applied for the design of a nonlinear controller for a continuously stirred tank reactor (CSTR). The statistical analysis of the results confirms that the proposed modified hybrid artificial bee colony (HMABC) achieves consistently better performance than the traditional ABC algorithm. The results are compared with conventional ABC and nonlinear PID (NLPID) to show the superiority of the proposed algorithm. The performance of the HMABC algorithm-based controller is competitive with other state-of-the-art meta-heuristic algorithm-based controllers in the literature.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137348
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-13 z 13

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