DNA Design Based on Improved Ant Colony Optimization Algorithm With Bloch Sphere

被引：4

作者：

Zhou, Qihang ^{[1
]}

Wang, Xiao ^{[2
]}

Zhou, Changjun ^{[1
]}

机构：

[1] Zhejiang Normal Univ, Coll Math & Comp Sci, Jinhua 321014, Zhejiang, Peoples R China

[2] Zhejiang Normal Univ, Xingzhi Coll, Jinhua 321004, Zhejiang, Peoples R China

来源：

IEEE ACCESS | 2021年 / 9卷

基金：

中国国家自然科学基金;

关键词：

DNA; Encoding; Image coding; Hamming distance; Biological cells; Heuristic algorithms; DNA computing; DNA design; bloch system; ant colony algorithm; HAMMING DISTANCE; CODES; CAPACITY; STORAGE; CONSTRUCTIONS; ENCRYPTION;

D O I：

10.1109/ACCESS.2021.3094876

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

DNA computing and coding have good application prospects in data storage, data computing, data encryption and other fields. Meanwhile, it is very important to design a set of DNA coding set that meets a variety of constraints in today's research. The purpose of DNA coding is to find as many qualified code sets as possible under given conditions or to keep each DNA code in the DNA code set as far as possible from other codes. The former is used in this paper. The algorithm uses the Bloch system to initialize the DNA coding population, and uses the Ant Colony Algorithm to find the optimal DNA coding. At the same time, crossover and mutation operations are added to make the generated population more random and diverse. Experimental results show that the number of code sets obtained by this algorithm under certain specific conditions is better than the number of code sets obtained by other algorithms.

引用

页码：104513 / 104521

页数：9

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