Day-Ahead Short-Term Forecasting Electricity Load via Approximation

Хамитов, Р. Н.; Gritsay, A. S.; Tyunkov, Dmitry; Sinitsin, G E

doi:10.1088/1757-899x/189/1/012005

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.

Day-Ahead Short-Term Forecasting Electricity Load via Approximation

Cited by 5 publications

References 8 publications

Performance characteristics describe the structure of descriptors

Performance characteristics describe the structure of descriptors

Short-term forecast methods of electricity generation by solar power plants and its classification

The Training Selection Method for Short-Term Prediction Electricity Loads with Criteria of Informativeness and Compactness

Contact Info

Product

Resources

About