- 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