Identifying novelties and anomalies for incremental learning in streaming time series forecasting

Author:

Melgar-García LauraORCID,Gutiérrez-Avilés DavidORCID,Rubio-Escudero Cristina,Troncoso AliciaORCID

Funder

Ministerio de Ciencia e Innovación

European Regional Development Fund

Junta de Andalucía

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference42 articles.

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3. Regional analytics and forecasting for most affected stock markets: The case of GCC stock markets during COVID-19 pandemic;Alkhatib;Int. J. Syst. Assur. Eng. Manag.,2022

4. Almeida, E., Ferreira, C., Gama, J., 2013. Adaptive Model Rules from Data Streams. In: Proceedings of the Machine Learning and Knowledge Discovery in Databases. pp. 480–492.

5. Online Machine Learning Algorithms over Data Streams;Benczúr,2019

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