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灰色系统理论在管道完整性数据预测中的应用 被引量:3

Application of Theory of Grey System on Forecasting the Pipeline IntegrityData
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摘要 根据管道完整性数据的不确定性、管道环境变化速度低、信息过去值发展受到的扰动少等特征,推荐采用基于趋势外推法的灰色系统理论预测管道完整性数据,提出了预测原则和预测对象分类等。介绍了预测数据序列生成步骤方法,给出了仅有一次检测数据的预测计算实例。 The trend extrapolation from theory of grey system to forecast pipeline integrity is recommended in this article,which is based on the uncertainty of integrity data of pipeline,low variety speed,of pipeline environment, little disturbed of data and other information,etc. Principle,classification and others to forecast the researched object are presented as well. The step and method of creating forecasting data series are also introduced,and a practical calculation example is given here which have detection data detected only once.
出处 《油气储运》 CAS 北大核心 2006年第5期26-28,共3页 Oil & Gas Storage and Transportation
关键词 管道 数据 完整性 灰色系统 预测 pipeline,data,integrity,grey system,forecast
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同被引文献20

  • 1李彬,秦燕,周劲.用模糊灰色理论评价管道腐蚀与防护态势[J].油气储运,2005,24(3):32-34. 被引量:6
  • 2谢乃明,刘思峰.离散GM(1,1)模型与灰色预测模型建模机理[J].系统工程理论与实践,2005,25(1):93-99. 被引量:352
  • 3李福琴.灰色模型的稳定性和建模精度研究[D].武汉:武汉理工大学理学院,2005.
  • 4宋巧娜,唐德善.基于灰色理论和BP神经网络的农业用水量预测[J].农机化研究,2007,29(9):53-55. 被引量:7
  • 5邓聚龙.灰色论基础.武汉:华中科技大学出版社,2002.
  • 6Junfeng Li, Aiping Yang , Wenzhan Dai. Modeling Mecha- nism of Grey Neural Network and Its Application [ C ]//Pro- ceedings of 2007 IEEE International Conference on Grey Systems and Intelligent Services, Nanjing, 2007: 404- 408.
  • 7Funahashi K. On the Approximate Realization of Continuous Mapping by neural Networks [ J ]. Neural Networks, 1989,2 (3) : 183-192.
  • 8Cristiano Cervellera, Aihong Wen, Victoria C P Chen. Neural network and regression spline value function ap- proximations for stochastic dynamic programming [ J ]. Computer & Operations Research, 2007, 34 ( 1 ) : 70-90.
  • 9LIU S F, DENG J L. The range suitable for GM (1, 1) [J]. The Journal of Grey System, 1999, 11 ( 1 ) .. 131-138.
  • 10ZENG X Y, XIAO X P. A research on morbidity problem in accumulating method GM ( 1, 1 ) model[C]. Guangzhou." ICMLC, 2005.

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