Application of improved intelligent ant colony algorithm in protein folding prediction

While the single ant colony algorithm and the fish swarm algorithm have many advantages, they also have various shortcomings. After analyzing the advantages and disadvantages of the ant colony algorithm and the fish swarm algorithm, this paper uses the complementary principle of the two algorithms t...

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Bibliographic Details
Main Authors: Fengjuan Wang, Cheng Xu, Shufeng Jiang, Fengxia Xu
Format: Article
Language:English
Published: SAGE Publishing 2020-07-01
Series:Journal of Algorithms & Computational Technology
Online Access:https://doi.org/10.1177/1748302620941411
Description
Summary:While the single ant colony algorithm and the fish swarm algorithm have many advantages, they also have various shortcomings. After analyzing the advantages and disadvantages of the ant colony algorithm and the fish swarm algorithm, this paper uses the complementary principle of the two algorithms to effectively fuse the two population intelligent algorithms. The improved swarm intelligence algorithm is applied to the well-considered protein folding prediction problem, and the simplified protein structure Toy model is verified, and the ideal results are obtained. The improved algorithm enhances the search ability, and the computational efficiency is greatly improved, ensuring the accuracy of the operation.
ISSN:1748-3026