NDLI: Load forecasting using elastic gradient descent

Content Provider	IEEE Xplore Digital Library
Author	Yuan Hong Changhao Xia Shixiang Zhang Lin Wu Chao Yuan Ying Huang Xuxu Wang Haifeng Zhu
Copyright Year	2013
Description	Author affiliation: Electr. & New Energy Coll., China Three Gorges Univ., Yichang, China (Yuan Hong; Changhao Xia; Shixiang Zhang; Lin Wu; Chao Yuan; Ying Huang; Xuxu Wang) \|\| Yichang Maintenance Div., Hubei Electr. Power Co., Yichang, China (Haifeng Zhu)
Abstract	The article describes in detail the theoretical basis of the elastic gradient descent method which combines the principal component analysis (PCA) and the time sequence method. In the short-term forecasting instance, the elastic gradient descent neural networks which combines the PCA and the time sequence method was used. The result verifies the effectiveness and feasibility of the introducing the PCA and the time sequence method in processing network optimization. The simulation result shows that this method has good prediction accuracy and convergence speed. In the long-term forecasting instance, the elastic gradient descent method which combines PCA method was used for that forecasting. The result indicated the superiority of the introducing the principal component analysis method in processing large amounts of data. As used herein, the model has good ductility and also lots of factors can be considered in. The prediction accuracy and generalization is good. And it will have a further application prospect in the actual forecast.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	247
Ending Page	251
File Size	319968
Page Count	5
File Format	PDF
ISBN	9781467347143
ISSN	21579563
DOI	10.1109/ICNC.2013.6817979
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Load forecasting Neural networks time sequence load forecasting Predictive models elastic gradient descent method Forecasting principal component analysis Principal component analysis Load modeling error back propagation artificial neural network
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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