Van Genuchten (VG) equation is the most commonly used equation of soil moisture characteristic curve, and the accuracy of its parameters directly affects the calculation accuracy of soil moisture motion equation. In order to obtain the parameters of the equation more accurately, this paper establishes an optimization model of the VG equation parameters. This optimization model uses the advantages of the cuckoo search algorithm and the differential evolution algorithm to combine the two into a new hybrid cuckoo search algorithm, namely DECS algorithm, and uses this algorithm to solve the parameter optimization problem of VG equation of soil moisture characteristic curve. By collecting and analyzing the relevant experimental data of various soil qualities, the dehumidification and moisture absorption curves of three different soil qualities were selected for simulation calculation. The results show that in the experiment of solving the parameter estimation problem of the VG equation, the DECS hybrid algorithm has better exploration and development capabilities than the cuckoo search algorithm. The hybrid algorithm has relatively significant performance in terms of calculation accuracy and convergence.

中文翻译：

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差分进化布谷鸟搜索算法在VG方程参数优化中的应用

Van Genuchten（VG）方程是最常用的土壤水分特征曲线方程，其参数的准确性直接影响土壤水分运动方程的计算精度。为了更准确地得到方程的参数，本文建立了VG方程参数的优化模型。该优化模型利用布谷鸟搜索算法和差分进化算法的优点将两者结合成一种新的混合布谷鸟搜索算法即DECS算法，并利用该算法求解土壤水分特征曲线VG方程的参数优化问题. 通过收集和分析各种土质的相关试验数据，选取三种不同土质的除湿吸湿曲线进行模拟计算。结果表明，在求解VG方程参数估计问题的实验中，DECS混合算法比布谷鸟搜索算法具有更好的探索和开发能力。混合算法在计算精度和收敛性方面具有比较显着的性能。