并在此基础上提出了基于差分演化算法的属性约简算法。
And on this basis, an attribute reduction algorithm based on the improved differential evolutionary algorithm was put forward.
采用差分演化算法对模型进行了参数优化并进行了计算机模拟。
A differential evolution algorithm was used to optimize the parameters of the model, and then the computer simulation has been carried out.
其中，差分演化算法在数值函数优化方面的性能要优于其它的优化算法。
The performance of DE algorithm is superior to other algorithm in numerical function optimization.
因此用进化策略、差分演化算法、泛函网络来研究数值计算，有较高的理论价值和实际意义。
So, researching numerical computing by Evolution Strategy, Differential Evolution Algorithm and Functional Networks have higher theory value and practical significance.
该方法对差分演化算法的操作算子进行改进，解决了差分演化算法生成离散型测试数据的问题。
This method ameliorated the operators of DE algorithm to avoid the discrete test data generation based on DE algorithm.
通过对差分演化算法的变异策略改进，使优化后的差分演化算法在函数优化方面性能得到进一步提高。
The mutation strategy was improved so that the optimized DE algorithm performance was further improved on function optimization.
通过对差分演化算法的变异策略改进，使优化后的差分演化算法在函数优化方面性能得到进一步提高。
The mutation strategy was improved so that the optimized DE algorithm performance was further improved on function optimization.
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