Memetic Computing SCIE

國(guó)際簡(jiǎn)稱：MEMET COMPUT 參考譯名：模因計(jì)算

主要研究方向：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-OPERATIONS RESEARCH & MANAGEMENT SCIENCE 非預(yù)警期刊審稿周期：

《模因計(jì)算》(Memetic Computing)是一本由Springer Berlin Heidelberg出版的以COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-OPERATIONS RESEARCH & MANAGEMENT SCIENCE為研究特色的國(guó)際期刊，發(fā)表該領(lǐng)域相關(guān)的原創(chuàng)研究文章、評(píng)論文章和綜述文章，及時(shí)報(bào)道該領(lǐng)域相關(guān)理論、實(shí)踐和應(yīng)用學(xué)科的最新發(fā)現(xiàn)，旨在促進(jìn)該學(xué)科領(lǐng)域科學(xué)信息的快速交流。該期刊是一本未開放期刊，近三年沒有被列入預(yù)警名單。該期刊享有很高的科學(xué)聲譽(yù)，影響因子不斷增加，發(fā)行量也同樣高。

2區(qū) 中科院分區(qū)
Q2 JCR分區(qū)
17 年發(fā)文量
3.3 IF影響因子
未開放 是否OA
26 H-index
2009 創(chuàng)刊年份
4 issues per year 出版周期
English 出版語言

Memes have been defined as basic units of transferrable information that reside in the brain and are propagated across populations through the process of imitation. From an algorithmic point of view, memes have come to be regarded as building-blocks of prior knowledge, expressed in arbitrary computational representations (e.g., local search heuristics, fuzzy rules, neural models, etc.), that have been acquired through experience by a human or machine, and can be imitated (i.e., reused) across problems.

The Memetic Computing journal welcomes papers incorporating the aforementioned socio-cultural notion of memes into artificial systems, with particular emphasis on enhancing the efficacy of computational and artificial intelligence techniques for search, optimization, and machine learning through explicit prior knowledge incorporation. The goal of the journal is to thus be an outlet for high quality theoretical and applied research on hybrid, knowledge-driven computational approaches that may be characterized under any of the following categories of memetics:

Type 1: General-purpose algorithms integrated with human-crafted heuristics that capture some form of prior domain knowledge; e.g., traditional memetic algorithms hybridizing evolutionary global search with a problem-specific local search.

Type 2: Algorithms with the ability to automatically select, adapt, and reuse the most appropriate heuristics from a diverse pool of available choices; e.g., learning a mapping between global search operators and multiple local search schemes, given an optimization problem at hand.

Type 3: Algorithms that autonomously learn with experience, adaptively reusing data and/or machine learning models drawn from related problems as prior knowledge in new target tasks of interest; examples include, but are not limited to, transfer learning and optimization, multi-task learning and optimization, or any other multi-X evolutionary learning and optimization methodologies.

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Memetic Computing期刊信息

ISSN：1865-9284
出版語言：English
是否OA：未開放
E-ISSN：1865-9292
出版地區(qū)：GERMANY
是否預(yù)警：否
出版商：Springer Berlin Heidelberg
出版周期：4 issues per year
創(chuàng)刊時(shí)間：2009
開源占比：0.0795
Gold OA文章占比：8.64%
OA被引用占比：0
出版國(guó)人文章占比：0.42
出版撤稿占比：0
研究類文章占比：100.00%

Memetic Computing CiteScore評(píng)價(jià)數(shù)據(jù)（2024年最新版）

CiteScore

SJR

SNIP

CiteScore 指數(shù)

6.8

0.945

1.1

學(xué)科類別	分區(qū)	排名	百分位
大類：Mathematics 小類：Control and Optimization	Q1	14 / 130	89%
大類：Mathematics 小類：General Computer Science	Q1	41 / 232	82%

名詞解釋：CiteScore 是衡量期刊所發(fā)表文獻(xiàn)的平均受引用次數(shù)，是在 Scopus 中衡量期刊影響力的另一個(gè)指標(biāo)。當(dāng)年CiteScore 的計(jì)算依據(jù)是期刊最近4年（含計(jì)算年度）的被引次數(shù)除以該期刊近四年發(fā)表的文獻(xiàn)數(shù)。例如，2022年的 CiteScore 計(jì)算方法為：2022年的 CiteScore =2019-2022年收到的對(duì)2019-2022年發(fā)表的文件的引用數(shù)量÷2019-2022年發(fā)布的文獻(xiàn)數(shù)量注：文獻(xiàn)類型包括：文章、評(píng)論、會(huì)議論文、書籍章節(jié)和數(shù)據(jù)論文。

Memetic Computing中科院評(píng)價(jià)數(shù)據(jù)

中科院 2023年12月升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	計(jì)算機(jī)科學(xué)	2區(qū)	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī)：人工智能 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 運(yùn)籌學(xué)與管理科學(xué)	2區(qū) 2區(qū)

中科院 2022年12月升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	計(jì)算機(jī)科學(xué)	3區(qū)	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī)：人工智能 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 運(yùn)籌學(xué)與管理科學(xué)	3區(qū) 3區(qū)

中科院 2021年12月舊的升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	計(jì)算機(jī)科學(xué)	3區(qū)	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī)：人工智能 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 運(yùn)籌學(xué)與管理科學(xué)	3區(qū) 3區(qū)

中科院 2021年12月基礎(chǔ)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	工程技術(shù)	2區(qū)	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī)：人工智能 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 運(yùn)籌學(xué)與管理科學(xué)	3區(qū) 3區(qū)

中科院 2021年12月升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	計(jì)算機(jī)科學(xué)	3區(qū)	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī)：人工智能 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 運(yùn)籌學(xué)與管理科學(xué)	3區(qū) 3區(qū)

中科院 2020年12月舊的升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	計(jì)算機(jī)科學(xué)	3區(qū)	OPERATIONS RESEARCH & MANAGEMENT SCIENCE 運(yùn)籌學(xué)與管理科學(xué) COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī)：人工智能	3區(qū) 4區(qū)

Memetic Computing JCR評(píng)價(jià)數(shù)據(jù)（2023-2024年最新版）

按JIF指標(biāo)學(xué)科分區(qū)	收錄子集	分區(qū)	排名	百分位
學(xué)科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	82 / 197	58.6%
學(xué)科：OPERATIONS RESEARCH & MANAGEMENT SCIENCE	SCIE	Q2	32 / 106	70.3%

按JCI指標(biāo)學(xué)科分區(qū)	收錄子集	分區(qū)	排名	百分位
學(xué)科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	86 / 198	56.82%
學(xué)科：OPERATIONS RESEARCH & MANAGEMENT SCIENCE	SCIE	Q2	38 / 106	64.62%

Memetic Computing歷年數(shù)據(jù)統(tǒng)計(jì)

影響因子

中科院分區(qū)

Memetic Computing中國(guó)學(xué)者發(fā)文選摘

1、An intelligent scheduling algorithm for complex manufacturing system simulation with frequent synchronizations in a cloud environment
Author: Feng Yao, Yiping Yao, Lining Xing, Huangke Chen, Zhongwei Lin, Tianlin Li

Journal: Memetic Computing, 2019, Vol., , DOI:10.1007/s12293-019-00284-3
2、Mathematical modeling and a discrete artificial bee colony algorithm for the welding shop scheduling problem
Author: Xinyu Li, Shengqiang Xiao, Cuiyu Wang, Jin Yi

Journal: Memetic Computing, 2019, Vol., , DOI:10.1007/s12293-019-00283-4
3、Project portfolio selection and scheduling under a fuzzy environment
Author: Xiaoxiong Zhang, Keith W. Hipel, Yuejin Tan

Journal: Memetic Computing, 2019, Vol., , DOI:10.1007/s12293-019-00282-5
4、A multi-level knee point based multi-objective evolutionary algorithm for AUC maximization
Author: Jianfeng Qiu, Minghui Liu, Lei Zhang, Wei Li, Fan Cheng

Journal: Memetic Computing, 2019, Vol., , DOI:10.1007/s12293-019-00280-7
5、DSM-DE: a differential evolution with dynamic speciation-based mutation for single-objective optimization
Author: Libao Deng, Lili Zhang, Haili Sun, Liyan Qiao

Journal: Memetic Computing, 2019, Vol., , DOI:10.1007/s12293-019-00279-0
6、Novel paralleled extreme learning machine networks for fault diagnosis of wind turbine drivetrain
Author: Xian-Bo Wang, Zhi-Xin Yang, Pak Kin Wong, Chao Deng

Journal: Memetic Computing, 2018, Vol., , DOI:10.1007/s12293-018-0277-2
7、An improved differential evolution algorithm for solving a distributed assembly flexible job shop scheduling problem
Author: Xiuli Wu, Xiajing Liu, Ning Zhao

Journal: Memetic Computing, 2018, Vol., , DOI:10.1007/s12293-018-00278-7
8、Improving artificial bee colony with one-position inheritance mechanism
Author: Xin Zhang, Shiu Yin Yuen

Journal: Memetic Computing, 2013, Vol.5, 187-211, DOI:10.1007/s12293-013-0117-3