基于智能算法和RETC软件的Van Genuchten方程参数估计

Xu Yang, Xue-yi You, Min Ji, Liuming Pan, Xiuduo Wang, Lejun Zhao
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引用次数: 1

摘要

为探索RETC软件和遗传算法、模拟退火算法、粒子群算法等智能算法对城市绿地土壤水分特征曲线Van Genuchten (VG)方程参数的优化效果,本研究采用张力计法获得绿地土壤干燥曲线,其中RETC软件、遗传算法、采用模拟退火算法和粒子群算法对VG方程的参数进行了重构。结果表明,在给定条件下,RETC软件和三种智能算法确定的VG方程参数拟合结果与实验结果非常接近,仿真精度非常高(R2=0.996),并且智能算法的拟合效果优于RECT软件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating Parameters of Van Genuchten Equation Based on Intelligent Algorithms and RETC Software
In order to explore optimization effects of RETC software and intelligent algorithms, including genetic algorithm, simulated annealing algorithm and particle swarm optimization, on parameters of Van Genuchten (VG)Equation for the soil water characteristic curve of urban green space, the soil drying curve of green space was obtained by using the tensiometer method in this study, where RETC software, genetic algorithm, simulated annealing algorithm and particle swarm optimization we reconstructed to solve parameters of VG Equation. The results indicated that the parameter fitting results of VG Equation determined by RETC software and three intelligent algorithms were very close to experimental results with a very high simulation accuracy (R2=0.996) in given conditions, moreover, the fitting effect of intelligent algorithms was better than that of RECT software.
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