从图4可以看出，除了函数F8和F9 ,随着迭代次数的增加， CCGOA

从图4可以看出，除了函数F8和F9 ,随着迭代次数的增加， CCGOA算法最优值逐渐向0靠近，且SR的结果均为100%，效果远好于GOA。CGOA在F1、F3、F4、F7、F10和F11的最优值逐渐向理论值靠近，SR值随着迭代次数增加逐渐上升到100%，与GOA相比函数结果较为明显，但是与CCGOA结果相对比结果较弱，CCGOA明显更有优势。因此可以进一步看出，采用Logistic混沌映射和云模型相结合对GOA性能有较大的改善，效果明显好于单独采用云模型的惯性权重对GOA的改进。

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目标语言: -

结果 (英语) 1: [复制]

复制成功！

As can be seen from Figure 4, except that the F9 function F8 and, as the number of iterations increases, CCGOA algorithm gradually approach the optimal value to 0, and SR 100% results, much better than GOA. CGOA in F1, F3, F4, F7, F10 and F11, the optimal value to gradually approach the theoretical value, SR value increases with the number of iterations is gradually increased to 100%, compared with the result of the function is obvious the GOA, but with opposite results CCGOA weaker results than, CCGOA obvious advantage. It can be further seen by Logistic chaotic map and cloud model combining GOA greater improved performance, significantly better than the inertia weight cloud model improvement of GOA alone.

正在翻译中..

结果 (英语) 2:[复制]

复制成功！

As can be seen from Figure 4, in addition to the functions F8 and F9, with the increase in the number of iterations, the optimal value of the CCGOA algorithm gradually approaches 0, and the result of SR is 100%, the effect is much better than GOA. The optimal values of CGOA in F1, F3, F4, F7, F10 and F11 gradually move closer to the theoretical value, the SR value gradually rises to 100% with the number of iterations, the function results are more obvious compared with GOA, but compared with the CCGOA results are relatively weak, CCGOA has obvious advantages. Therefore, it can be further seen that the use of Logistic chaos mapping and cloud model combination of goA performance has a great improvement, the effect is significantly better than the use of cloud model inertiaweight to improve GOA.

正在翻译中..

结果 (英语) 3:[复制]

复制成功！

As can be seen from Figure 4, except for functions F8 and F9, with the increase of the number of iterations, the optimal value of ccgoa algorithm gradually approaches 0, and the results of SR are all 100%, which is far better than Goa. The optimal value of CGOA in F1, F3, F4, F7, F10 and F11 gradually approaches to the theoretical value, and the SR value gradually rises to 100% with the increase of iterations. Compared with Goa, the function result is more obvious, but compared with ccgoa, the result is weaker, and ccgoa has more advantages. Therefore, it can be further seen that the combination of Logistic chaotic mapping and cloud model can greatly improve the performance of Goa, which is significantly better than the improvement of Goa by using the inertial weight of cloud model alone.<br>

正在翻译中..

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