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Forecasting Primary Energy Requirements of Territories by Autoregressive Integrated Moving Average and Backpropagation Neural Network Models
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-04
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Forecasting energy data, especially the primary energy requirement, is the key part of policy-making.
For those territories of different developing types, seeking a knowledge-based and dependable forecasting model is an essential prerequisite for the prosperous development of policy-making.
In this paper, both autoregressive integrated moving average and backpropagation neural network models which have been proved to be very efficient in forecasting are applied to the forecasts of the primary energy consumption of three different developing types of territories.
It is shown that the average relative errors between the actual data and simulated value are from 4.5% to 5.9% by the autoregressive integrated moving average and from 0.04% to 0.47% by the backpropagation neural network.
Specially, this research shows that the backpropagation neural network model presents a better prediction of primary energy requirement when considering gross domestic product, population, and the particular values as predictors.
Furthermore, we indicate that the single-input backpropagation neural network model can still work when the particular values have contributed most to the energy consumption.
American Psychological Association (APA)
Pan, Ning-Kang& Lv, Chunwan. 2019. Forecasting Primary Energy Requirements of Territories by Autoregressive Integrated Moving Average and Backpropagation Neural Network Models. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1200879
Modern Language Association (MLA)
Pan, Ning-Kang& Lv, Chunwan. Forecasting Primary Energy Requirements of Territories by Autoregressive Integrated Moving Average and Backpropagation Neural Network Models. Mathematical Problems in Engineering No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1200879
American Medical Association (AMA)
Pan, Ning-Kang& Lv, Chunwan. Forecasting Primary Energy Requirements of Territories by Autoregressive Integrated Moving Average and Backpropagation Neural Network Models. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1200879
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1200879