说实话，在计算机科学的一些主要分支学科的命名上就可以看出生物学的影子，譬如人工神经网络，遗传算法和进化计算法等等。
Indeed, the names of major subfields of computer science-such as artificial neural networks, genetic algorithms, and evolutionary computation-attest to the influence of biological analogies.
遗传算法是一种模拟自然进化而提出的简单高效的优化组合方法。
Genetic algorithms is an efficiently combined and optimized method by simulating the nature evolution.
随机梯度遗传算法进化代数从5增加到10以及从10增加到15时，三个航速下的目标识别率按照接近20%的比例增加。
Target recognition rates, under the three speeds, increase by about 20% in evolutional generation(EG) ranges, of SGGA, from 5 to 10 and from 10 to 15.
比照传统遗传算法与生物界进化过程，分析了引起传统遗传算法收敛速度慢和寻优效率低的两个原因。
By contrasting the traditional genetic algorithms (TGA) with the biologic evolution, two kinds of reasons that the convergence speed and searching efficiency in TGA are both lower are concluded.
比照传统遗传算法与生物界进化过程，分析了引起传统遗传算法收敛速度慢和寻优效率低的两个原因。
By contrasting the traditional genetic algorithms (TGA) with the biologic evolution, two kinds of reasons that the convergence speed and searching efficiency in TGA are both lower are concluded.
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