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金属矿山 ›› 2015, Vol. 44 ›› Issue (04): 178-181.

• 矿山测量 • 上一篇    下一篇

高斯函数模型在变形监测数据处理中的应用

王江荣   

  1. 兰州石化职业技术学院信息处理与控制工程系,甘肃 兰州 730060
  • 出版日期:2015-04-15 发布日期:2015-08-04
  • 基金资助:

    * 甘肃省科技厅项目(编号:1204GKCA004),甘肃省财政厅专项资金项目(编号:甘财教[2013]116号)。

Application of the Gauss Function Model in Data Processing of Deformation Monitoring

Wang Jiangrong   

  1. Department of Information Processing and Control Engineering, Lanzhou Petrochemical College of Vocational Technology,Lanzhou 730060,China
  • Online:2015-04-15 Published:2015-08-04

摘要: 建立了一种结构简单、精确度高、可操作性强的大坝变形数据高斯函数预测模型,克服了已有方法的不足。建模时利用MATLAB 遗传算法工具箱的主要函数ga()求出模型系数的初始值,再用搜索工具箱中的fminsearch 函数求出模型系数的最终值。用16期观测数据建模,再用4期变形数据对模型进行检验,检验结果表明所建模型具有很高的精确度,预测效果远好于已有的一些预测模型,为变形预测提供了一种新方法、新思路。

关键词: 变形预测, 高斯函数, 遗传算法, MATLAB

Abstract: With characteristics of simple structure,high precision,and high operability,a gauss function model of predicting deformation data for dams is set up to overcome the shortcomings of the existing methods.The main function of ga() in the genetic algorithm toolbox(MATLAB) is adopted to calculate the initial value of model coefficient,and then the fminsearch function in search toolbox is used to obtain the final value of model coefficient.16 sets of observation data are used to make modeling,and 4 groups of deformation data are used to test the model.The testing results show that the model has high accuracy,and its prediction is far better than other existing prediction model.This new model provides a new method and new idea for deformation prediction.

Key words: Deformation prediction, Gaussian function, Genetic algorithm, MATLAB