DocumentCode :
527585
Title :
The oil transmission station operational guidance calculation algorithm based on Hopfield neural network
Author :
Gao Weixin ; Nan, Tang ; Yaping, Li ; Huade, Zhang
Author_Institution :
Sch. of Electr. Eng., Xi´´an Shiyou Univ., Xi´´an, China
Volume :
2
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
716
Lastpage :
719
Abstract :
This paper proposes a connected graph for describing the technology flow of the oil transmission station. By classifying the nodes of the connected graph, the problem of deciding the operation procedures for a specific scheduled task can be translated to the problem of calculating a radial sub-graph of the connected graph. We present a mathematical model for oil transmission station optimal operation based on the connected graph. And we put forward Hopfield neural network for calculating the model. The energy function is also given in the paper. Real calculation shows that the method presented is practical.
Keywords :
Hopfield neural nets; graph theory; oil technology; scheduling; Hopfield neural network; connected graph; energy function; mathematical model; oil transmission station; operational guidance calculation algorithm; optimal operation; radial subgraph; scheduled task; technology flow; Geometry; Mathematical model; Petroleum; Pipelines; Schedules; Substations; Valves; Graph theory; Neural network; Oil transmission substation; component;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5583285
Filename :
5583285
Link To Document :
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