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2021年最新SCI期刊影响因子查询系统

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Genetic Programming and Evolvable Machines 期刊详细信息

基本信息
期刊名称 Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines
期刊ISSN 1389-2576
期刊官方网站 http://www.springer.com/computer/ai/journal/10710
是否OA
出版商 Springer New York
出版周期 Quarterly
始发年份
年文章数 17
最新影响因子 2.522(2021)
中科院SCI期刊分区
大类学科 小类学科 Top 综述
工程技术4区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能4区
COMPUTER SCIENCE, THEORY & METHODS 计算机:理论方法4区
CiteScore
CiteScore排名 CiteScore SJR SNIP
学科 排名 百分位 2.00 0.302 0.894
Mathematics
Theoretical Computer Science
35 / 118 70%
Computer Science
Hardware and Architecture
56 / 152 63%
Computer Science
Software
156 / 360 56%
Computer Science
Computer Science Applications
225 / 569 60%
补充信息
自引率 12.50%
H-index 32
SCI收录状况 Science Citation Index Expanded
官方审稿时间
网友分享审稿时间 数据统计中,敬请期待。
PubMed Central (PML) http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1389-2576%5BISSN%5D
投稿指南
期刊投稿网址 https://www.editorialmanager.com/genp/default.aspx
收稿范围
The journal of Genetic Programming and Evolvable Machines is devoted to reporting innovative and significant progress in automatic evolution of software and hardware. Methods for artificial evolution of active components, such as programs or machines, are rapidly developing branches of adaptive computation and adaptive engineering. They entail the development, evaluation and application of methods that mirror the process of neo-Darwinian evolution and produce as a result computational expressions such as algorithms or machines such as mechanical or electronic devices that actively process environmental information and transform their environment. In addition to its main topics, the journal covers related topics such as evolutionary algorithms with variable-size genomes, alternate methods of program induction, approaches to engineering systems development based on embryology, morphogenesis or other techniques inspired by adaptive natural systems.

Methods:

Genetic Programming; Variable-size evolutionary algorithms; Induction of algorithms and symbolic expressions by iterative and non-deterministic search; Evolutionary design and Optimization of electronic circuits and mechanical devices; On-line adaptation of hardware and software; Evolutionary robotics; DNA computing; Coevolutionary techniques; Meta-learning; Hybrid systems; Cellular and Developmental approaches.

Task Domains:

Algorithm evolution; Agents; Architecture; Art and animation; Classification and pattern recognition; Computer graphics; Computing; Circuit design; Data mining; Distributed problem solving; Engineering design applications; Games; Hardware and software testing and verification; Image and signal processing; Interactive evolution; Molecular biology applications; Music; Natural language processing; Network routing; Optimization; Process control; Robotics and motor control; Self-repair; Self-reproduction of software and hardware, Self-programming; System modeling.

Both theoretical papers (preferably including computer simulations) and application papers are welcome. Papers describing hardware implementations are strongly encouraged. Papers in the areas of artificial life, molecular computing and any other emergent computation technique will be considered as well.
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