基于鸟群算法的土壤水分特征曲线模型参数估算

Parameter estimation of soil moisture characteristic curve model based on bird swarm algorithm

本文提出了基于鸟群算法的Van Genuchten模型参数求解方法,并结合实测数据,对参数估算结果和精度进行分析评价。结果表明:基于鸟群算法(BSA)的参数估算方法获得的土壤残余含水率θr均比单纯形调优法(SEM)和非线性最小二乘法(NLS)的估算结果大11. 99%。基于鸟群算法精度要优于传统的单纯形调优法和非线性最小二乘法。鸟群算法可作为估计Van Genuchten模型参数的一种新方法。

The method of solving the parameters of Van Genuchten model based on the bird swarm algorithm is proposed in the paper. The estimated results and precision of the parameters are analyzed and evaluated based on the measured data. The results show that the soil residual moisture content θr obtained by the parameter estimation method based on the bird swarm algorithm （BSA） is higher than the estimation results 11.99% of simplex tuning method （SEM） and nonlinear least squares （NLS）. The precision based on the bird swarm algorithm is superior to the traditional simplex tuning method and nonlinear least square method. The bird swarm algorithm can be used as a new method to estimate the model parameters of Van Genuchten.