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Wyszukujesz frazę "Bai, Y. S." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Population diversity maintenance in brain storm optimization algorithm
Autorzy:
Cheng, S.
Shi, Y.
Qin, Q.
Zhang, Q
Bai, R.
Powiązania:
https://bibliotekanauki.pl/articles/91571.pdf
Data publikacji:
2014
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
brainstorm
optimization algorithm
convergence
divergence
brainstorm optimization
BSO
swarm intelligence
BSO algorithm
Opis:
The convergence and divergence are two common phenomena in swarm intelligence. To obtain good search results, the algorithm should have a balance on convergence and divergence. The premature convergence happens partially due to the solutions getting clustered together, and not diverging again. The brain storm optimization (BSO), which is a young and promising algorithm in swarm intelligence, is based on the collective behavior of human being, that is, the brainstorming process. The convergence strategy is utilized in BSO algorithm to exploit search areas may contain good solutions. The new solutions are generated by divergence strategy to explore new search areas. Premature convergence also happens in the BSO algorithm. The solutions get clustered after a few iterations, which indicate that the population diversity decreases quickly during the search. A definition of population diversity in BSO algorithm is introduced in this paper to measure the change of solutions’ distribution. The algorithm’s exploration and exploitation ability can be measured based on the change of population diversity. Different kinds of partial reinitialization strategies are utilized to improve the population diversity in BSO algorithm. The experimental results show that the performance of the BSO is improved by part of solutions re-initialization strategies.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 2; 83-97
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Event-related desynchronization/synchronization-based volitional cursor control in a two-dimensional center-out paradigm
Autorzy:
Huang, D.
Qian, K.
Oxenham, S.
Fei, D. -Y.
Bai, O.
Powiązania:
https://bibliotekanauki.pl/articles/1396737.pdf
Data publikacji:
2012
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
brain-computer interface
BCI
two-dimensional
two-dimensional BCI control
event-related synchronization
event-related desynchronization
EEG
Opis:
To achieve a reliable two-dimensional control by noninvasive EEG-based brain-computer interface (BCI), users are typically required to receive long-term training to learn effective regulation of their brain rhythmic activities, and to maintain sustained attention during the operation. We proposed a two-dimensional BCI using event-related desynchronization and event-related synchronization associated with human natural behavior so that users need neither long-term training nor high mental loads to maintain concentration. In this study, we intended to further investigate the performance of the proposed BCI associated with either physical movement or motor imagery with an online two-dimensional centerout cursor control paradigm. Model adaptation method was employed for better decoding of human movement intention from EEG activities. The results demonstrated an effective center-out cursor control: as high as 77.1% during online control with physical movement and 57.3% with motor imagery. It suggests that two-dimensional BCI control can be achieved without long-term training.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 2; 97-108
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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