Ensemble Transfer Learning for Time Series Forecasting: a Sensitivity Analysis Framework for a Shallow Neural Network

Kambale, Witesyavwirwa Vianney; Deeb, Ali; Benarbia, Taha; Salem, Mohamed; Machot, Fadi Al; Kyamakya, Kyandoghere

doi:10.1109/cscc58962.2023.00040

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Ensemble Transfer Learning for Time Series Forecasting: a Sensitivity Analysis Framework for a Shallow Neural Network

Cited by 3 publications

References 15 publications

On-the-fly training architecture for a time-series neural network on ADITYA/ADITYA-U data

On-the-fly training architecture for a time-series neural network on ADITYA/ADITYA-U data

Transformers in Time Series Forecasting: A brief Analysis of the Autoformer Transfer Learning Performance

Ensemble Transfer Learning for Time Series Forecasting: A Comparative Sensitivity Analysis of Two Shallow Networks

Contact Info

Product

Resources

About