煤炭工程 ›› 2015, Vol. 47 ›› Issue (7): 117-119.doi: 10.11799/ce201507038

• 研究探讨 • 上一篇    下一篇

基于PSO算法的概率积分法预计参数反演

徐孟强1,查剑锋1,李怀展2   

  1. 1. 中国矿业大学环境与测绘学院
    2. 中国矿业大学 环测学院;江苏省资源环境信息工程重点实验室
  • 收稿日期:2015-04-20 修回日期:2015-05-14 出版日期:2015-07-10 发布日期:2015-07-15
  • 通讯作者: 徐孟强 E-mail:1213547819@qq.com

Research on Parameters Inversion in Probability Integral Method by Particle Swarm Optimization

  • Received:2015-04-20 Revised:2015-05-14 Online:2015-07-10 Published:2015-07-15

摘要: 运用PSO算法设计了概率积分法预计参数反演程序,通过设计实验,对PSO算法反演概率积分法预计参数的可靠性、抗粗差干扰能力、抗观测点缺失能力及对初值的依赖性等四个方面进行研究。结果表明:运用PSO算法可以准确的反演出概率积分法预计参数,算法对随机误差和测点缺失有较强的抗干扰能力。在给定初值误差不大于10%时,初次反演结果令人满意;初值误差不大于50%时,下沉系数和主要影响角正切反演结果,不受初值影响。进一步分析表明,将反演参数二次回带重新反演可获得较为准确的结果,同时,适当增加初始种群规模,可提高参数反演的准确性和可靠性。

关键词: PSO算法, 概率积分法, 参数反演, 设计实验

Abstract: Abstract:Based on the PSO algorithm to design the inversion program of prediction parameters of proba-bility integral method. By designing experiments, these four experiments ,including the study of reliability of the PSO algorithm, resisting the effect of gross errors, the losses of observation points and the reliance on initial value are researched.The results show that the use of PSO algorithm can accurately inverse the prediction parameters of probability integral method ,which has a strong anti-interface ablility to the influences of random errors in observed values and the losses of observation points. When the given initial values’ error is no more than 10%, the first inversion can get satisfactory results; When the initial error is no more than 50%,the inversion result of subsidence coefficient and the main affect of tangent is not affected by initial value. Further analysis show that putting inversion parameters into the second inverse can get a more accurate results. Meanwhile, moderately increasing the scales of the initial population can improve the reliability and accuracy of parameter inversion.

Key words: psoalgorithm, probability integral method, parameter inversion, design of experiment

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