A Hybrid Forecasting Model Based on EMD-GASVM-RBFNN for Power Grid Investment Demand
Joint Authors
Li, Jinchao
Zhu, Shaowen
Wu, Qianqian
Zhang, Pengfei
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-26
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Power grid as an important infrastructure which ensures the healthy development of economy and society and accurate and reasonable prediction of the power grid investment demand has always been the focus problem of the power planning department and the power grid enterprises.
In view of the complex nonlinear and nonstationary characteristics of the power grid investment demand sequence, a novel hybrid EMD-GASVM-RBFNN forecasting model based on empirical mode decomposition (EMD) method, support vector machines optimized by genetic algorithm (GA-SVM) model, and radial basis function neural network (RBFNN) model is proposed.
Firstly, the EMD method is used to decompose the original power grid investment data sequence into a series of IMF components and a residual component which have stronger regularity compared with the original data.
Then, according to the different characteristics of each subsequence, the GA-SVM and RBFNN model will be used to forecast different subsequences, respectively.
Next, the prediction results of different subsequences are aggregated to obtain the final prediction results of the power grid investment.
Finally, this paper dynamically simulates China’s power grid investment from 2018 to 2020 based on the EMD-GASVM-RBFNN hybrid forecasting model and Monte Carlo method.
American Psychological Association (APA)
Li, Jinchao& Zhu, Shaowen& Wu, Qianqian& Zhang, Pengfei. 2018. A Hybrid Forecasting Model Based on EMD-GASVM-RBFNN for Power Grid Investment Demand. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1208852
Modern Language Association (MLA)
Li, Jinchao…[et al.]. A Hybrid Forecasting Model Based on EMD-GASVM-RBFNN for Power Grid Investment Demand. Mathematical Problems in Engineering No. 2018 (2018), pp.1-17.
https://search.emarefa.net/detail/BIM-1208852
American Medical Association (AMA)
Li, Jinchao& Zhu, Shaowen& Wu, Qianqian& Zhang, Pengfei. A Hybrid Forecasting Model Based on EMD-GASVM-RBFNN for Power Grid Investment Demand. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1208852
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208852