Title :
Prediction of Energy Production and Energy Consumption based on BP Neural Networks
Author :
Wei, Li ; Yumin, Shang
Author_Institution :
Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding
Abstract :
Nowadays, China has become a major energy consumer, and more importantly, however, China is also a major energy producer. With the development of economy, energy production and energy consumption has increased progressively year by year. In the context of the global energy supply pressure of the growing tension, energy and environmental situation is not optimistic, this paper starting from the unification of energy production and energy consumption constructed a new prediction method of BP neural networks, through making use of the energy industry statistical data, apply the BP neural networks to the prediction system, accurately predict the development and changing of energy production and energy consumption. Numerical results demonstrate the validity of the prediction method of BP neural networks.
Keywords :
backpropagation; electric power generation; neural nets; power consumption; power engineering computing; BP neural networks; China; energy consumer; energy consumption; energy industry; energy production prediction; global energy supply pressure; Artificial neural networks; Economic forecasting; Energy conservation; Energy consumption; Energy management; Environmental economics; Neural networks; Power generation economics; Prediction methods; Production systems; BP neural networks; energy consumption; energy production; error; prediction;
Conference_Titel :
Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on
Print_ISBN :
978-1-4244-3530-2
Electronic_ISBN :
978-1-4244-3531-9
DOI :
10.1109/KAMW.2008.4810454