NDLI: Approach to Daily Load Forecast of VSNN Based on Data Mining

Content Provider	IEEE Xplore Digital Library
Author	Niu Dong-Xiao Gu Zhi-Hong Xing Mian Wang Hui-Qing
Copyright Year	2007
Description	Author affiliation: North China Electr. Power Univ., Beijing (Niu Dong-Xiao; Gu Zhi-Hong)
Abstract	The keys of improving the precision of daily load forecasting lie in the fore processing and the forecasting model, so this paper puts forward a new method of vary structure neural network (shorten as "VSNN") for power load forecast which is based on united data mining technology. Firstly, to search the historical daily load which have the same meteorological category as the forecasting day; secondly, to make further collection of data to compose data sequence with highly similar meteorological features which can boost up rules and weaken disturbance; thirdly, to constitute VSNN forecasting model accordingly. So the model can overcome the disadvantages of ANN through vary structure optimization to determine the optimal structure and optimal fitting approximation, and it does not easily convergence, not easily trap in partial minimum, and its structure can be determined by itself not by artificially. In the end, the forecasting precision was improved effectively, the input and calculation model was simplified properly, and the software programming was easier to realize. So the new method is more practical.
Starting Page	363
Ending Page	368
File Size	197763
Page Count	6
File Format	PDF
ISBN	9781424407361
DOI	10.1109/ICIEA.2007.4318432
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Load forecasting Data mining Weather forecasting Meteorology Predictive models Technology forecasting Artificial neural networks Power system modeling Neural networks Meteorological factors
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Short-term load forecasting method based on structural neural network

Research on Power System Load Forecasting Model Based on Data Mining Technology

Data mining based neural network model for load forecasting

Energy and peak load forecast models using neural network for fast developing area

Information Entropy Based Neural Network Model for Short-Term Load Forecasting

Short-Term Load Forecasting Model For Power System Based on Complementation of Fuzzy-Rough Set Theory And BP Neural Network

Research on the Application of the Wavelet Neural Network Model in Peak Load Forecasting Considering of the Climate Factors

Study on Short Term Load Forecast based on Cloud Model

Determination of similar days in load forecast based on Grey incidence theory

Approach to Daily Load Forecast of VSNN Based on Data Mining

Similar Documents

Short-term load forecasting method based on structural neural network

Research on Power System Load Forecasting Model Based on Data Mining Technology

Data mining based neural network model for load forecasting

Energy and peak load forecast models using neural network for fast developing area

Information Entropy Based Neural Network Model for Short-Term Load Forecasting

Short-Term Load Forecasting Model For Power System Based on Complementation of Fuzzy-Rough Set Theory And BP Neural Network

Research on the Application of the Wavelet Neural Network Model in Peak Load Forecasting Considering of the Climate Factors

Study on Short Term Load Forecast based on Cloud Model

Determination of similar days in load forecast based on Grey incidence theory

Approach to Daily Load Forecast of VSNN Based on Data Mining