首页> 外文会议>Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on >Partially computed fitness function based genetic algorithm for hydrophobic-hydrophilic model
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Partially computed fitness function based genetic algorithm for hydrophobic-hydrophilic model

机译:基于部分适应度函数的遗传算法的疏水-亲水模型

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Fitness computation after each crossover or mutation operation in genetic algorithm (GA) requires computational time that increases with the increasing length of the chromosome. In this paper, an efficient GA is proposed for protein folding prediction based on the hydrophobic-hydrophilic (HP) model. The partial fitness of the parent computed from one end of sequence till crossover or mutation point is utilized for the computation of the fitness of the child. The calculated value of the partial fitness is stored with the corresponding chromosome. Although the approach requires additional memory for each hydrophobic residue of each chromosome, the computation time is reduced significantly, which is more important than the memory overhead.
机译:遗传算法(GA)中每次交叉或变异操作后的适应度计算都需要随着染色体长度的增加而增加的计算时间。本文提出了一种有效的遗传算法,用于基于疏水-亲水(HP)模型的蛋白质折叠预测。从序列的一个末端到交叉或突变点为止计算出的父母的部分适应度被用于计算孩子的适应度。部分适应度的计算值与相应的染色体一起存储。尽管该方法需要为每个染色体的每个疏水残基增加存储空间,但计算时间却大大减少,这比存储开销更为重要。

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