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传统的参数化多元组合算子模型在进行对数变换后,采用最小二乘法求解模型参数。在满足构建的优化目标函数条件下,直接用基于群集智能的混合蛙跳算法对参数化组合算子模型中的参数进行优化,避免了传统解法过程中需要进行的对数变换,因而使参数求解变得简化。改进后的参数化组合算子模型被应用于地下水水质评价,其评价结果与用其他多种方法的评价结果基本一致。从而表明:混合蛙跳算法优化得出的地下水水质评价参数化组合算子模型为地下水水质评价提供了一种简便和实用的新方法。
The traditional parameterized multivariate combinatorial operator model is solved logarithmically by the method of least squares. Under the condition of satisfying the optimized objective function, the parameters of the parameterized combinatorial operator model are optimized by using the hybrid frog-leap algorithm based on cluster intelligence directly, which avoids the logarithm transformation needed in the traditional solution process, Become simplified. The improved parameterized combinatorial operator model is applied to groundwater quality assessment, and its evaluation results are basically consistent with those of other methods. It is shown that the parameterized combinatorial operator model of groundwater quality evaluation, which is obtained by the hybrid frog leaping algorithm, provides a simple and practical new method for groundwater quality evaluation.