最后用一个简单的实例说明了使用遗传算法生成基本数据类型测试数据的过程。
At last we use a simple example to show the process of test data of basic type generation with GA.
将BP神经网络和遗传算法相结合运用于快速设计的结构优化问题。
BP neural networks and GA were applied to the optimal design of mechanical structure.
实验结果证明采用遗传算法是很有效的。
The experimental results show that the GA approach is efficient.
并且与针法进行了比较，结果表明遗传算法是一种有效的算法。
Compared with Needle Algorithm, the result showed that GA was effective.
遗传算法主要的特点在于：简单、通用、鲁棒性强。
The main characteristic of the GA is that it is simple, universal and robust.
最后对遗传算法在CAD中的应用作了展望。
研究了基于遗传算法的固体发动机壳体工艺流程面向成本优化问题。
GA to resolve process route optimization of solid rocket motor shell is studied.
采用遗传算法生成最终测试数据。
最后运用遗传算法求解了该问题。
最后运用遗传算法求解了该问题。
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