.png){kind=icon}
返回
A genetic algorithm for community detection in complex networks
.png){kind=icon}
PRE
AI
DOI：10.1007/s11771-013-1611-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A new genetic algorithm for community detection in complex networks was proposed. It adopts matrix encoding that enables traditional crossover between individuals. Initial populations are generated using nodes similarity, which enhances the diversity of initial individuals while retaining an acceptable level of accuracy, and improves the efficiency of optimal solution search. Individual crossover is based on the quality of individuals' genes; all nodes unassigned to any community are grouped into a new community, while ambiguously placed nodes are assigned to the community to which most of their neighbors belong. Individual mutation, which splits a gene into two new genes or randomly fuses it into other genes, is non-uniform. The simplicity and effectiveness of the algorithm are revealed in experimental tests using artificial random networks and real networks. The accuracy of the algorithm is superior to that of some classic algorithms, and is comparable to that of some recent high-precision algorithms.
Keyword:
complex networks
community detection
genetic algorithm
matrix encoding
nodes similarity
期刊
IF:
4.4
论文数:
5.2K
被引数:
1.0W
机构
引用论文
Alterations in the balance of protein kinase and phosphatase activities and age‐related impairments of synaptic transmission and long‐term potentiation.png)
Hippocampus
HippocampusIF0
PREAI
分享收藏Laboratory methods for assessing vaccine potency retained in aerosol outputs from nebulizers: Application to World Health Organization measles aerosol project评估气雾发生器输出气溶胶中疫苗效价保留量的实验室方法：在WHO麻疹气雾项目中的应用Vaccine
VaccineIF0
PREAI
分享收藏The Mobile Robot for Garbage Sorting and Handling Based on Machine Vision2021 IEEE International Conference on Artificial Intelligence, Robotics, and Communication (ICAIRC)
2021 IEEE International Conference on Artificial Intelligence, Robotics, and Communication (ICAIRC)IF0
PREAI
分享收藏Using Seawater Reverse Osmosis (SWRO) desalting system for less environmental impacts in Qatar在卡塔尔使用海水反渗透 (SWRO) 脱盐系统减少环境影响Desalination
DesalinationIF0
PREAI
分享收藏
查看更多内容