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Wyświetlanie 1-15 z 18
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
Powiązania:
https://bibliotekanauki.pl/articles/762833.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
Atterberg limits, artificial bee colony, artificial neural networks, support vector machine, regression tree
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.
Źródło:
Polish Journal of Soil Science; 2018, 51, 2
0079-2985
Pojawia się w:
Polish Journal of Soil Science
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.
Powiązania:
https://bibliotekanauki.pl/articles/376463.pdf
Data publikacji:
2019
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
parallel computing
Artificial Bee Colony
PMSM
state feedback
controller
MATLAB/Simulink
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.
Źródło:
Poznan University of Technology Academic Journals. Electrical Engineering; 2019, 100; 145-156
1897-0737
Pojawia się w:
Poznan University of Technology Academic Journals. Electrical Engineering
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.
Powiązania:
https://bibliotekanauki.pl/articles/384141.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
combinatorial interaction testing
pair-wise testing
covering array
artificial bee colony
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.
Źródło:
e-Informatica Software Engineering Journal; 2016, 10, 1; 9-29
1897-7979
Pojawia się w:
e-Informatica Software Engineering Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Particle swarm optimization and discrete artificial bee colony algorithms for solving production scheduling problems
Autorzy:
Witkowski, Tadeusz
Powiązania:
https://bibliotekanauki.pl/articles/298169.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Tematy:
Discrete Artificial Bee Colony
particle swarm optimization (PSO)
production scheduling problem
makespan
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.
Źródło:
Technical Sciences / University of Warmia and Mazury in Olsztyn; 2019, 22(1); 61-74
1505-4675
2083-4527
Pojawia się w:
Technical Sciences / University of Warmia and Mazury in Olsztyn
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:
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:
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:
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:
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:
Short-term optimal energy management in stand-alone microgrid with battery energy storage
Autorzy:
Paliwal, N. K.
Singh, A. K.
Singh, N. K.
Powiązania:
https://bibliotekanauki.pl/articles/140998.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial bee colony
battery energy storage
clean energy sources
optimal energy management
stand-alone microgrid
Opis:
The optimal energy management (OEM) in a stand-alone microgrid (SMG) is a challenging job because of uncertain and intermittent behavior of clean energy sources (CESs) such as a photovoltaic (PV), wind turbine (WT). This paper presents the effective role of battery energy storage (BES) in optimal scheduling of generation sources to fulfill the load demand in an SMG under the intermittency of theWT and PV power. The OEM is performed by minimizing the operational cost of the SMG for the chosen moderate weather profile using an artificial bee colony algorithm (ABC) in four different cases, i.e. without the BES and with the BES having a various level of initial capacity. The results show the efficient role of the BES in keeping the reliability of the SMG with the reduction in carbon-emissions and uncertainty of the CES power. Also, prove that the ABC provides better cost values compared to particle swarm optimization (PSO) and a genetic algorithm (GA). Further, the robustness of system reliability using the BES is tested for the mean data of the considered weather profile.
Źródło:
Archives of Electrical Engineering; 2018, 67, 3; 499--513
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
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:
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:
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:
Zastosowanie algorytmów rojowych do optymalizacji parametrów w modelach układów regulacji
Application of swarm intelligence algorithms to optimization of control system models
Autorzy:
Tomera, M.
Powiązania:
https://bibliotekanauki.pl/articles/269153.pdf
Data publikacji:
2015
Wydawca:
Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
Tematy:
algorytmy rojowe
optymalizacja parametrów
algorytm mrówkowy
algorytm sztucznej kolonii pszczół
algorytm optymalizacji rojem cząstek
swarm intelligence
swarm based optimization
ant colony optimization
Artificial Bee Colony
particle swarm optimization (PSO)
Opis:
W pracy przedstawione zostały algorytmy rojowe, takie jak: algorytm mrówkowy, zmodyfikowany algorytm mrówkowy, algorytm sztucznej kolonii pszczół oraz algorytm optymalizacji rojem cząstek. Dla tych algorytmów przygotowane zostało oprogramowanie w Matlabie, pozwalające na optymalizację parametrów poszukiwanych modeli matematycznych, wyznaczanych na podstawie przeprowadzonych testów identyfikacyjnych lub na optymalizację parametrów regulatorów zastosowanych w modelach matematycznych układów sterowania.
The paper presents the swarm intelligence algorithms, such as: ant colony algorithm (ACO), the modified ant colony algorithm (MACO), the artificial bee colony algorithm (ABC) and the particle swarm optimization algorithm (PSO). Ant colony optimization (ACO) based upon the observation of the behavior of ant colonies looking for food in the surrounding anthill. Feeding ants it is based on finding the shortest path transitions between a food source and the anthill. In the process of foraging ants on their paths crossing from the nest to a food source and back, they leave a pheromone trail. The work presents also the modified ant colony algorithm (MACO). This algorithm is based on searching the solution space surrounded by the best solution obtained in the previous iteration. If you find a local minimum, the proposed algorithm uses pheromone to find a new solution space, while retaining the position information current local minimum. The artificial bee colony algorithm is one of the well-known swarm intelligence algorithms. In the past decade there has been created several different algorithms based on the observation of the behavior of cooperative bees. Among them, the most frequently analyzed and used is bee algorithm proposed in 2005 by Dervis Karaboga and was be used in the proposed paper. The particle swarm optimization algorithm (PSO) is based on adjusting the change speed of the moving particles to a speed of particles movement in the neighborhood. Particle optimization algorithm is one of the computational techniques derived on the basis of swarm behavior such as flocks of birds and schools of fish, which is the basis for the functioning of the exchange of information to enable them to cooperate. It was noticed that the animals in the herd tend to maintain the optimum distance from their neighbors, by appropriate adjustment of their speed. This method allows the synchronous and collision-free motion, often accompanied by sudden changes of direction and due to the rearrangement of the optimal formation. For these algorithms has been prepared the software in Matlab, allowing to optimization of the mathematical models designated on the basis of the carried out identification tests and control parameters used in the mathematical model of the control system.
Źródło:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2015, 46; 97-102
1425-5766
2353-1290
Pojawia się w:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
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