【摘要】 遗传算法(geneticalgorithm,GA)作为一种自适应启发式概率性迭代式全局搜索算法,具有不依赖于问题模型的特性、全局最优性、隐含并行性、高效性、解决不同非线性问题的鲁棒性特点,目前已经广泛应用于自动控制、机器人学、计算机科学、模式识别、模糊人工神经和工程优化等设计领域。本文首先介绍了GA的基本原理,即搜索的基本过程;随后总结了GA与传统算法相比所具有的优点;第三部分则分别综述了GA在蛋白质结构预测中主要使用的模型、设计和执行策略,以及使用GA与其他算法相互结合预测蛋白质结构的研究进展;最后提出了作者对GA研究中存在问题的认识和研究展望。更多还原

【Abstract】 Genetic algorithm GA is parameter search procedures which simulate the nature evolution procedures. As an effective global optimization tool GA takes all the advantages during its applications such as simple operation generalization robustness and parallelism. And now GA had applied into autocontrol automatonolgy computer science engineering optimization etc.. This paper presents the origin mechanics and features of GA at first. And then the emphases on the summarization on the progress about protein structure model construction predicting tactic and the combination research with the other artificial intelligence technique were reviewed. Finally the problem and prospect of genetic algorithm in predicting protein structure was also put forward.更多还原