DocumentCode
2008090
Title
The artificial neural networks for real-time operation of natural gas production and sale
Author
Wang, Xiao-Lin ; Xiao, Jian-zhong
Author_Institution
Sch. of Econ. & Manage., China Univ. of Geosci., Wuhan, China
Volume
3
fYear
2010
fDate
17-18 July 2010
Firstpage
314
Lastpage
316
Abstract
Backpropagation neural networks (BPNN) is introduced in this paper to explore the non-linear relationship between planned gas supply and actual gas demand from uneven coefficients of natural gas demands of end-users with a case study of North China Branch of Sinopec, aiming to solve the imbalances between gas supply and demand and instabilities of gas operation from uncertainties of natural gas demmand fluctuation with daily or seasonal change The research indicates that BPNN could effectively build up complex non-linear map between the planned supply and actual demand in the process of natural gas production and sale in uperstream gas fields, and give the feasible guide to the real-time operation for the gas field production and sale, providing a novel intelligent method and new idea for the operation decision-making of natural gas.
Keywords
backpropagation; decision making; natural gas technology; supply and demand; BPNN; North China Branch of Sinopec; actual gas demand; artificial neural networks; backpropagation neural networks; decision-making; gas field production; gas field sale; gas operation; intelligent method; natural gas demand fluctuation; natural gas demands; natural gas production; natural gas sale; nonlinear map; planned gas supply; uperstream gas fields; Backpropagation; Educational institutions; Heating; artificial neural networks; natural gas; production and sale; real-time operation;
fLanguage
English
Publisher
ieee
Conference_Titel
Environmental Science and Information Application Technology (ESIAT), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-7387-8
Type
conf
DOI
10.1109/ESIAT.2010.5568330
Filename
5568330
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