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Wyszukujesz frazę "bee algorithm" wg kryterium: Wszystkie pola


Wyświetlanie 1-16 z 16
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:
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:
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:
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:
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:
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:
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:
Novel nature-inspired autonomous guidance of aerial robots formation regarding honey bee artificial algorithm and fuzzy logic
Autorzy:
Shafieenejad, Iman
Powiązania:
https://bibliotekanauki.pl/articles/2055040.pdf
Data publikacji:
2020
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
nature-inspired guidance
honey bee swarm
optimal trajectory
aerial robot
fuzzy logic
Opis:
In this article, a novel nature-inspired autonomous guidance is investigated regarding the honey bee motion algorithm for aerial robots and fuzzy logic. Combination of the bee al- gorithm and fuzzy logic is proposed to achieve an on-line guidance for methodology of this research. The main idea of this work belongs to a novel analogy between honey bees and aerial robots motions. Moreover, information links between the aerial robots are demon- strated to construct a formation of vehicles by updating motions based on fuzzy decision making. Three dimensional simulations for the aerial robots are considered to show the ef- ficient performance of autonomous guidance. The simulation results show precise ability of the proposed method for aerospace and robotics engineers based on a nature phenomenon to present an innovative guidance method.
Źródło:
Journal of Theoretical and Applied Mechanics; 2020, 58, 3; 791--798
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
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
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:
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:
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:
Identification of Bee Colony Acoustic Signals using the Dynamic Time Warping Algorithm
Autorzy:
Polyniak, Yu.
Fedasyuk, D.
Marusenkova, Tetyana
Powiązania:
https://bibliotekanauki.pl/articles/972922.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Oddział w Lublinie PAN
Tematy:
Acoustic Signal
Signal Recognition
Dynamic Time Warping
Fast Fourier Transform
Automated Bee Colony Monitoring
Opis:
The work deals with automated recognition of the current state of a bee colony, for continuous monitoring of processes running in a bee hive is of key importance in beekeeping. The dynamic time warping algorithm is considered as a method of analyzing acoustic signals produced by a bee colony. Upon such an analysis one can make inferences about the current state of the colony. We have developed a software module for audio-signal identification, which is to be used as a part of an automated bee colony monitoring system, and a software tool for verification of the module. We evaluated the efficacy of the algorithm, the probability of bee colony states correctly recognized using acoustic signals produced by the colony and consumed computational resources by the example of a queen bee’s sounds recorded during swarming. The dependencies of the signal processing time and the successful pattern recognition probabilities on the frame sample rate and frame size are presented.
Źródło:
ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes; 2019, 8, 4; 19-27
2084-5715
Pojawia się w:
ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
Dostawca treści:
Biblioteka Nauki
Artykuł
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