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Wyświetlanie 1-3 z 3
Tytuł:
Systemic Evolutionary Algorithm inspired by the methods of quantum computing to improve the accuracy of the model on the neuronal motion the end of the robot arm PR–02
Autorzy:
Wołynka, Ł.
Tchórzewski, J.
Powiązania:
https://bibliotekanauki.pl/articles/97323.pdf
Data publikacji:
2016
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
Evolution algorithms
Quantum computing
Modeling systems
Robot PR–02
Artificial Neural Networks
Environment MATLAB and Simulink
Opis:
The article contains selected results of research on the design Systemic Evolutionary Algorithm inspired by quantum informatics methods and description how to implement it in Matlab language in order to use for improve parameters neural model on example robot robot PR–02 arm motion. Initial population was based on weights matrix of artificial neural network. Randomly selected population of individual chromosomes in both the initial and in the following parent population have been converted to binary values, and these to quantum values by using created for this purpose quatization() function. Quantum gene value was determined on the basis of stonger pure state represented by different chromosomes, to which dequantization() function was used. Selection of individuals was conducted based on the model of neural robot PR–02 motion implemented in Matlab language using calculationsNeuralNetworks() function.
Źródło:
Computer Applications in Electrical Engineering; 2016, 14; 297-312
1508-4248
Pojawia się w:
Computer Applications in Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Systemic Evolutionary Algorithm inspired by methods of Quantum computer sciences for the improvement of the accuracy of neural models in electrical engineering and electrical power engineering
Autorzy:
Tchórzewski, J.
Powiązania:
https://bibliotekanauki.pl/articles/97692.pdf
Data publikacji:
2016
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
Evolutionary Algorithms
Quantum computer science
Quantum mixed number
Systems modelling
Robot PR–02
Artificial Neural Networks
MATLAB and Simulink environment
Electric Power Exchange
Opis:
The work contains selected results of research on the application of quantum computer science to a systemic evolutionary algorithm for the purpose of improving accuracy of neural models in electrical engineering and electrical power engineering. Artificial neural networks are used in neural modeling, which networks are designed and taught models of systems using available numerical data. Parameters of neural networks, and especially, elements of weight matrices, biases as well as parameters of activation functions may be improved using evolutionary algorithms. It seems that applying solutions offered by quantum computer science to systemic evolutionary algorithm, and especially, as regards creation of quantum initial population, quantum crossover and mutation operators as well as selection, considerably improves the accuracy of modelling, which was verified in MATLAB and Simulink environment using selected examples such as RP–02 robot’s arm movement, the development of the Polish Electrical Power Exchange (polish: TGEE) system, etc.
Źródło:
Computer Applications in Electrical Engineering; 2016, 14; 280-296
1508-4248
Pojawia się w:
Computer Applications in Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Neural model of the vehicle control system in a racing game. Part 1, Design and its implementation
Autorzy:
Tchórzewski, Jerzy
Bolesta, Arkadiusz
Powiązania:
https://bibliotekanauki.pl/articles/2175160.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
Artificial Neural Networks
Godot Engine
MATLAB
Simulink environment
CLion IDE
video games
Opis:
The publication consist of two parts. Part 1 contains the results of research on the design, learning and implementation of the Perceptron Artificial Neural Network as a model of neural control of car movement on the racetrack. This part 1 presents the results of studies, including review of the methods used in video racing games from the point of view of the selection of a method that can be used in the own research experiment, selection of the Artificial Neural Network architecture, its teaching method and parameters for the intended research experiment, selection of the data measurement method to be used in ANN training, as well as development design of a car game, its implementation and conducting simulation tests. In designing the game of vehicle traffic on the racetrack, among others, Godot Engine game engine and MATLAB and Simulink programming environment. The numerical data (14 input quantities and two output quantities) for ANN training were prepared with the use of semi-automatic measurement of the race track control points. Part 2 shows i.a. the results of the testing and simulation experiments that confirm the correct functioning of both the game and the model of the neural control system. There were also shown, among others, the possibility of continuing research in the field of increasing the flexibility of the racing game, in particular the flexibility of the vehicle traffic control system through the use of other artificial intelligence methods, such as ant algorithms or evolutionary algorithms.
Źródło:
Studia Informatica : systems and information technology; 2022, 1(26); 23--44
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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