Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Efficient Algorithms for Time Series Prediction Method. / Rakitskiy, Anton.
2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON). Institute of Electrical and Electronics Engineers (IEEE), 2022. p. 120-123.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Efficient Algorithms for Time Series Prediction Method
AU - Rakitskiy, Anton
N1 - This research was supported by Russian Science Foundation.
PY - 2022
Y1 - 2022
N2 - This paper describes the effective algorithms for calculating the Krichevsky measure and the R measure which are used in the time series prediction method. This prediction method is based on universal coding and first was proposed in 1988. The reliability and potential of method’s application was investigated in the context of many real tasks, however, the prediction calculation speed was the main problem. The algorithms proposed in the work allow to calculate the predicted value online and have the minimum possible complexity which significantly expands the possibilities of applying the method itself.
AB - This paper describes the effective algorithms for calculating the Krichevsky measure and the R measure which are used in the time series prediction method. This prediction method is based on universal coding and first was proposed in 1988. The reliability and potential of method’s application was investigated in the context of many real tasks, however, the prediction calculation speed was the main problem. The algorithms proposed in the work allow to calculate the predicted value online and have the minimum possible complexity which significantly expands the possibilities of applying the method itself.
UR - https://www.scopus.com/inward/record.url?eid=2-s2.0-85147493044&partnerID=40&md5=dbde343cf7a030893540cfa04fae3a8e
UR - https://www.mendeley.com/catalogue/9b05bbfc-350f-3152-a1aa-5032ccfcb4f6/
U2 - 10.1109/sibircon56155.2022.10016954
DO - 10.1109/sibircon56155.2022.10016954
M3 - Conference contribution
SN - 9781665464802
SP - 120
EP - 123
BT - 2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)
PB - Institute of Electrical and Electronics Engineers (IEEE)
T2 - 2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2022
Y2 - 11 November 2022 through 13 November 2022
ER -
ID: 45959103