DocumentCode :
2096922
Title :
Parallel Intelligent Decision Supporting System of Underground Powerhouse Construction of Large Hydroelectric Power Station
Author :
Jiang Annan ; Su Guoshao ; Ru Zhongliang
Author_Institution :
Coll. of Traffic & Logistics Eng., Maritime Univ., Dalian, China
fYear :
2010
fDate :
28-31 March 2010
Firstpage :
1
Lastpage :
4
Abstract :
Large hydraulic underground powerhouse in construction is a complex dynamic process, the decision of construction could neither depend on mechanical computing nor experience exclusively. It has significant sense to construct automatic, integrative and expeditious decision supporting system. The paper constructs a basic frame combing data base, knowledge base, model base and referring machine based on parallel computing technique. Based on the frame, an intelligence decision supporting system combing mechanical calculation and experience analysis methods has been developed. The object-oriented programming is carried out and the visual software is developed. It is shown feasible from its application in Shuibuya underground powerhouse of China.
Keywords :
decision support systems; hydroelectric power stations; object-oriented programming; power engineering computing; China; Shuibuya underground powerhouse; experience analysis methods; intelligence decision supporting system combing; large hydraulic underground powerhouse; large hydroelectric power station; mechanical calculation; mechanical computing; object-oriented programming; parallel computing technique; parallel intelligent decision supporting system; underground powerhouse construction; Concurrent computing; Feedback; Intelligent systems; Machine intelligence; Object oriented modeling; Parallel processing; Power engineering and energy; Power engineering computing; Power generation; Power system modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
Type :
conf
DOI :
10.1109/APPEEC.2010.5448565
Filename :
5448565
Link To Document :
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