基于改进果蝇算法的概率积分法预计参数反演

    Prediction parameters inversion of the probability integral method based on the improved fruit flies algorithm

    • 摘要: 由于概率积分法函数模型的非线性表现形式以及各参数之间的相关性,概率积分法开采沉陷预计参数反演时存在计算复杂、易发散、容易陷入局部最优解等问题。利用参数设置少、计算效率高、算法实现容易、全局寻优能力强且精度较高的果蝇算法进行基于概率积分法的开采沉陷预计参数反演,并对算法进行改进。以实测下沉值为参照,将预计结果与实测值相比较,结果表明,改进的果蝇算法对概率积分法的开采沉陷预计参数反演具有适用性,对于用概率积分法进行开采沉陷预计的精度的提高有一定的积极作用。

       

      Abstract: Because of the non-linear representation of the function model of probability integral method and the correlation between the parameters,there are some problems in mining subsidence prediction parameters inversion of probability integral method such as complicated calculation, easy divergence, easy to fall into local optimum and so on.Fruit flies algorithm with low parameter setting, high calculation efficiency, easy implementation, strong global optimization ability and high precision is used for inversion of mining subsidence prediction parameters based on probability integral method, the algorithm is also improved.With the measured sinking value as the reference, the predicted results are compared with the measured values.The results show that the improved fruit flies algorithm is applicable to the prediction parameters inversion of mining subsidence by probability integral method.It has positive effect on improving the prediction precision of mining subsidence by probability integral method.

       

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