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pro vyhledávání: '"Junzhu Ma"'
Autor:
Junzhu Ma
Publikováno v:
7TH INTERNATIONAL CONFERENCE ON MATHEMATICS: PURE, APPLIED AND COMPUTATION: Mathematics of Quantum Computing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee328eaa130d8330bec73e6664a6dfe8
https://doi.org/10.1063/5.0117723
https://doi.org/10.1063/5.0117723
Publikováno v:
ICACI
Kernel recursive least-squares (KRLS) has shown better predictive energy efficiency in time series prediction. However, in complex and non-stationary environment, there are still some problems of low prediction efficiency and accuracy. In view of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2f0f107bcf19e39a185c92f99026315
https://doi.org/10.1109/icaci49185.2020.9177519
https://doi.org/10.1109/icaci49185.2020.9177519
Publikováno v:
Engineering Applications of Artificial Intelligence. 91:103547
With the deepening of the research on kernel recursive least squares (KRLS), significant researches have been applied to time series online prediction. However, it usually ignores the extraneous and redundant factors in the raw data, which can cause
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e642c47116d586f8ca38361f489f830d
https://doi.org/10.1016/j.engappai.2020.103547
https://doi.org/10.1016/j.engappai.2020.103547
Publikováno v:
2018 Ninth International Conference on Intelligent Control and Information Processing (ICICIP).
Kernel recursive least squares algorithm is widely employed in online prediction of time series as a kernel expend method. In the process of recursive updating, it has a lower computational complexity and a fewer storage memory. However, with the add
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::635a3feafbda1ec990420e1187d70f73
https://doi.org/10.1109/icicip.2018.8606696
https://doi.org/10.1109/icicip.2018.8606696