An embedding-based non-stationary fuzzy time series method for multiple output high-dimensional multivariate time series forecasting in IoT applications-Reference-Cited by-同舟云学术

An embedding-based non-stationary fuzzy time series method for multiple output high-dimensional multivariate time series forecasting in IoT applications

Published:2022-12-22 Issue:13 Volume:35 Page:9407-9420
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Bitencourt Hugo Vinicius,Orang Omid^ORCID,de Souza Luiz Augusto Facury,Silva Petrônio C. L.^ORCID,Guimarães Frederico Gadelha^ORCID

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Fundação de Amparo á Pesquisa do Estado de Minas Gerais

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-08120-5.pdf

Reference48 articles.

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2. Miorandi D, Sicari S, De Pellegrini F, Chlamtac I (2012) Internet of things: vision, applications and research challenges. Ad Hoc Netw 10(7):1497–1516

3. Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of things (iot): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660

4. Ditzler G, Roveri M, Alippi C, Polikar R (2015) Learning in nonstationary environments: a survey. IEEE Compt Int Mag 10(4):12–25

5. Xu D, Shi Y, Tsang IW, Ong Y-S, Gong C, Shen X (2020) Survey on multi-output learning. IEEE Trans Neural Netw Learn Syst 31(7):2409–2429

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