期刊文献+

因素分析法在观测数据处理上的应用 被引量:3

Integral analysis method and its application to observational data of dam
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摘要 本文应用因素分析法进行大坝监测数据的整体分析,文中讨论了数学模型、因素提取的特征值法、旋转变换与因素解释等问题.计算示例表明,确能从大量观测数据中提取出含义明确的关键因素,它们与坝体变形性质吻合;由因素分析模型复制得到的数据与原数据很接近,有很高的相关系数;利用因素分析还能对观测数据进行检错、校正与补缺. The factor analysis method including mathematical model, eigenvalue method of factor abstraction, rotational transformation and factor explanation, and its application to integral analysis of observational data of large dam have been presented in this paper. Results show that the critical factors abstracted can reflect the deformation characteristics of arch dam. Data reproduced from factor analysis well coincide with the original observational data and errors in observation can also be detected and corrected.
出处 《水利学报》 EI CSCD 北大核心 1998年第5期28-32,共5页 Journal of Hydraulic Engineering
基金 国家自然科学基金
关键词 大坝监测 因素分析法 数据处理 dam observation, factor analysis, integral analysis of data.
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参考文献4

  • 1李富强,1997年
  • 2团体著者,紧水滩水电站大坝监测资料分析报告,1993年
  • 3谢小庆,因素分析,1989年
  • 4汪树玉,大坝观测与土工测试

同被引文献22

  • 1马福恒,刘成栋.大坝安全评价中的信息赋权模型[J].水电自动化与大坝监测,2005,29(3):68-70. 被引量:9
  • 2于静江,周春晖.过程控制中的软测量技术[J].控制理论与应用,1996,13(2):137-144. 被引量:147
  • 3Riedmiller M, Braun H. A direct adaptive method for faster backpropagation learning: the RPROP algorithm [ A]. Proceedings of the IEEE International Conference on Neural Networks [ C ]. New York:IEEE Press, 1993. 586 -591.
  • 4Chen S, Billings S A. Neural networks for nonlinear dynamic system modeling and identification [J]. International Journal of Control, 1992, 56(2) : 359 -366.
  • 5Su H B, Fan L T, Schlup J R. Monitoring the process of curing of epoxy/graphite fiber composites with a recurrent neural network as a soft sensor [ J ]. Engineering Applications of Artificial Intelligence, 1998,11(2) : 293 -306.
  • 6Park S Y, Hart C H. A nonlinear soft sensor based on multivariate smoothing procedure for quality estimation in distillation columns[ J ]. Computers and Chemical Engineering, 2000,24 ( 2 - 7 ) :871 - 877.
  • 7Baum E B, Haussler D. What size net gives valid generalization[J]. Neural Computation, 1998,1(1 ) :151 - 160.
  • 8SL244-98.水库洪水调度考评规定[S].[S].,..
  • 9Chen S, Billings S A. Neural networks for nonlinear dynamic system modeling and identification [ J]. International Journal of Control, 1992, 56(2): 359 -366.
  • 10Su H B, Fan L T, Schlup J R. Monitoring the process of curing of epoxy/graphite fiber composites with a recurrent neural network as a soft sensor [ J ]. Engineering Applications of Artificial Intelligence, 1998,11 (2): 293 ~ 306.

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