Application of improved intelligent ant colony algorithm in protein folding prediction. (July 2020)

• Record Type: Journal Article
• Authors: Wang, Fengjuan; Xu, Cheng; Jiang, Shufeng; Xu, Fengxia
• Is Part Of: Journal of algorithms & computational technology. Volume 14(2020)
• Publication Date: 2020-07
• Subjects: Ant colony algorithm -- fish swarm algorithm -- fusion of intelligent algorithms -- two-dimensional Toy model -- protein folding prediction; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/1748302620941411
• Languages: English
• ISSNs: 1748-3018

Abstract

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.