AnIO: anchored input–output learning for time-series forecasting
Author:
Funder
Operational Program Competitiveness, Entrepreneurship and Innovation
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09175-8.pdf
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2. Fatima S, Uddin M (2022) On the forecasting of multivariate financial time series using hybridization of DCC-GARCH model and multivariate ANNs. Neural Comput Appl 34(24):21911–21925
3. Hamzaçebi C, Es HA, Çakmak R (2019) Forecasting of turkey’s monthly electricity demand by seasonal artificial neural network. Neural Comput Appl 31:2217–2231
4. Li R, Chen X, Balezentis T, Streimikiene D, Niu Z (2021) Multi-step least squares support vector machine modeling approach for forecasting short-term electricity demand with application. Neural Comput Appl 33:301–320
5. Torres J, Martínez-Álvarez F, Troncoso A (2022) A deep LSTM network for the Spanish electricity consumption forecasting. Neural Comput Appl 34(13):10533–10545
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