【摘要】 针对传统的开采沉陷预计方法，在求取预计参数时存在计算量烦琐、精度低、速度慢等缺陷，本文开展了基于狮群算法（LSO）的概率积分预计参数反演方法研究。LSO是一种群体智能算法，该算法已在光伏最大功率跟踪中方面得到广泛的应用，至今尚未发现应用于矿山开采沉陷预计领域中。为了准确获取预计参数，本文将LSO应用于概率积分参数反演中，以此构建基于LSO的概率积分预计参数反演方法。研究结果表明：(1)仿真实验：反演参数q、tanβ、b、θ的反演参数中误差分别为0.032 5、0.118 8、0.028 5、1.067 8且4个反演参数相对误差最大值均小于4.90%；拐点偏移距S_a、S_b、S_c、S_d反演参数中误差均小于6.8，反演参数相对误差均小于2.90%。(2)应用实例：利用基于LSO的概率积分预计参数反演方法求解淮南矿区顾桥矿1414(1）工作面的概率积分预计参数，求取参数结果分别为：q=1.10;tanβ=1.82;b=0.35；θ=86.62°；S_a=-3.20 m;S_b=-5.12 m;S_c=59.28 m;S_d=43.45 m；下沉值与水平移动值拟合中误差为122.76 mm，满足工程要求。更多还原

【Abstract】 Aiming at the disadvantages of traditional mining subsidence prediction methods such as cumbersome calculations,low accuracy,and slow speed in obtaining prediction parameters,this paper carried out a research on the inversion method of probability integral prediction parameters based on lion swarm optimization(LSO).LSO is a swarm intelligence algorithm,which has been widely used in photovoltaic maximum power tracking,and has not been found to be used in mining subsidence prediction.In order to obtain the predicted parameters accurately,this paper applied LSO to the inversion of probability integral parameters,in order to construct an LSO-based inversion method of probability integral predicted parameters.Research indicates:(1)Simulation experiment:the errors of of the inversion parameters q,tanβ，b andθare0.032 5,0.118 8,0.028 5,1.067 8respectively,and the maximum relative errors of the four inversion parameters are all less than4.90%;the inflection point offsets S_a.The errors of S_b,S_c,S_dinversion parameters are all less than6.8,and the relative errors of inversion parameters are all less than2.90%.(2)Application example:using the LSO-based probability integral prediction parameter inversion method to solve the probability integral prediction parameters of the1414(1)working surface of Guqiao Mine in Huainan Mining area,the results of the parameters are as follows:q=1.10,tanβ=1.82,b=0.35，θ=86.62°，S_a=-3.20m,S_b=-5.12m,S_c=59.28m,S_d=43.45m,the error in fitting the sinking value and the horizontal movement value is122.76mm,which meets engineering requirements.更多还原