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Swarm Intelligence Q3

期刊收录：
SCIE
Scopus

基本信息

期刊ISSN：
1935-3812
期刊简拼：
SWARM INTELL-US
年发文章数：
9
E-ISSN：
1935-3820
Gold OA文章占比
45.24%
研究文章占比：
100.00%
是否OA：
No
Jcr分区：
Q3
中科院分区：
4区

出版信息

出版商：
Springer US
涉及研究方向：
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ROBOTICS
出版国家：
UNITED STATES
出版语言：
English
出版周期：
4 issues per year
出版年份：
2007

2023-2024最新影响因子:2.1
自引率:4.80%
五年影响因子:2.8
JCI期刊引文指标:0.7
h-index:32
CiteScore:5.70

期刊关键词

3区 SCIE Scopus 计算机科学 4区 COMPUTER SCIENCE ARTIFICIAL INTELLIGENCE 计算机：人工智能 ROBOTICS 机器人学

期刊简介

Swarm Intelligence is the principal peer-reviewed publication dedicated to reporting on research

and developments in the multidisciplinary field of swarm intelligence. The journal publishes

original research articles and occasional review articles on theoretical, experimental and/or

practical aspects of swarm intelligence. All articles are published both in print and in electronic

form. There are no page charges for publication. Swarm Intelligence is published quarterly.

The field of swarm intelligence deals with systems composed of many individuals that coordinate

using decentralized control and self-organization. In particular, it focuses on the collective

behaviors that result from the local interactions of the individuals with each other and with their

environment. It is a fast-growing field that encompasses the efforts of researchers in multiple

disciplines, ranging from ethology and social science to operations research and computer

engineering.

Swarm Intelligence will report on advances in the understanding and utilization of swarm

intelligence systems, that is, systems that are based on the principles of swarm intelligence. The

following subjects are of particular interest to the journal:

• modeling and analysis of collective biological systems such as social insect colonies, flocking

vertebrates, and human crowds as well as any other swarm intelligence systems;

• application of biological swarm intelligence models to real-world problems such as distributed

computing, data clustering, graph partitioning, optimization and decision making;

• theoretical and empirical research in ant colony optimization, particle swarm optimization,

swarm robotics, and other swarm intelligence algorithms.