当前位置：首页 SCI期刊 SCIE期刊计算机科学中科院3区 JCRQ2 期刊介绍(非官网)

International Journal Of Machine Learning And CyberneticsSCIE

国际简称：INT J MACH LEARN CYB 参考译名：国际机器学习与控制论杂志

中科院分区
3区
CiteScore分区
Q1
JCR分区
Q2

基本信息：: ISSN：1868-8071; E-ISSN：1868-808X; 是否OA：未开放; 是否预警：否; TOP期刊：否

出版信息：: 出版地区：GERMANY; 出版商：Springer Berlin Heidelberg; 出版语言：English; 出版周期：12 issues per year; 出版年份：2010; 研究方向：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

评价信息：: 影响因子：3.1; H-index：30; CiteScore指数：7.9; SJR指数：0.988; SNIP指数：1.217

发文数据：: Gold OA文章占比：3.75%; 研究类文章占比：99.66%; 年发文量：295; 自引率：0.1071...; 开源占比：0.037; 出版撤稿占比：0; 出版国人文章占比：0.56; OA被引用占比：0.0215...

投稿咨询加急见刊

英文简介期刊介绍 CiteScore数据中科院SCI分区 JCR分区发文数据常见问题

英文简介International Journal Of Machine Learning And Cybernetics期刊介绍

Cybernetics is concerned with describing complex interactions and interrelationships between systems which are omnipresent in our daily life. Machine Learning discovers fundamental functional relationships between variables and ensembles of variables in systems. The merging of the disciplines of Machine Learning and Cybernetics is aimed at the discovery of various forms of interaction between systems through diverse mechanisms of learning from data.

The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid dissemination of the latest advancements in the area. The emphasis of IJMLC is on the hybrid development of machine learning and cybernetics schemes inspired by different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications. New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC.

Key research areas to be covered by the journal include:

Machine Learning for modeling interactions between systems

Pattern Recognition technology to support discovery of system-environment interaction

Control of system-environment interactions

Biochemical interaction in biological and biologically-inspired systems

Learning for improvement of communication schemes between systems

期刊简介International Journal Of Machine Learning And Cybernetics期刊介绍

《International Journal Of Machine Learning And Cybernetics》自2010出版以来，是一本计算机科学优秀杂志。致力于发表原创科学研究结果，并为计算机科学各个领域的原创研究提供一个展示平台，以促进计算机科学领域的的进步。该刊鼓励先进的、清晰的阐述，从广泛的视角提供当前感兴趣的研究主题的新见解，或审查多年来某个重要领域的所有重要发展。该期刊特色在于及时报道计算机科学领域的最新进展和新发现新突破等。该刊近一年未被列入预警期刊名单，目前已被权威数据库SCIE收录，得到了广泛的认可。

该期刊投稿重要关注点：

预计审稿时间：
计算机科学
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
SCIE
中科院3区
非预警

Cite Score数据（2024年最新版）International Journal Of Machine Learning And Cybernetics Cite Score数据

CiteScore：7.9
SJR：0.988
SNIP：1.217

学科类别	分区	排名	百分位
大类：Computer Science 小类：Computer Vision and Pattern Recognition	Q1	21 / 106	80%
大类：Computer Science 小类：Software	Q1	85 / 407	79%
大类：Computer Science 小类：Artificial Intelligence	Q1	84 / 350	76%

CiteScore 是由Elsevier(爱思唯尔)推出的另一种评价期刊影响力的文献计量指标。反映出一家期刊近期发表论文的年篇均引用次数。CiteScore以Scopus数据库中收集的引文为基础，针对的是前四年发表的论文的引文。CiteScore的意义在于，它可以为学术界提供一种新的、更全面、更客观地评价期刊影响力的方法，而不仅仅是通过影响因子(IF)这一单一指标来评价。

历年Cite Score趋势图

中科院SCI分区International Journal Of Machine Learning And Cybernetics 中科院分区

中科院 2023年12月升级版 综述期刊：否 Top期刊：否

大类学科	分区	小类学科	分区
计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

中科院分区表 是以客观数据为基础，运用科学计量学方法对国际、国内学术期刊依据影响力进行等级划分的期刊评价标准。它为我国科研、教育机构的管理人员、科研工作者提供了一份评价国际学术期刊影响力的参考数据，得到了全国各地高校、科研机构的广泛认可。

中科院分区表 将所有期刊按照一定指标划分为1区、2区、3区、4区四个层次，类似于“优、良、及格”等。最开始，这个分区只是为了方便图书管理及图书情报领域的研究和期刊评估。之后中科院分区逐步发展成为了一种评价学术期刊质量的重要工具。

历年中科院分区趋势图

JCR分区International Journal Of Machine Learning And Cybernetics JCR分区

2023-2024 年最新版

按JIF指标学科分区	收录子集	分区	排名	百分位
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	86 / 197	56.6%

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	84 / 198	57.83%

JCR分区的优势在于它可以帮助读者对学术文献质量进行评估。不同学科的文章引用量可能存在较大的差异，此时单独依靠影响因子(IF)评价期刊的质量可能是存在一定问题的。因此，JCR将期刊按照学科门类和影响因子分为不同的分区，这样读者可以根据自己的研究领域和需求选择合适的期刊。

历年影响因子趋势图

发文数据

2023-2024 年国家/地区发文量统计

国家/地区数量
CHINA MAINLAND467
India63
Iran39
Australia27
USA27
Canada17
England17
Turkey14
Saudi Arabia12
Taiwan12

本刊中国学者近年发表论文

1、Learning relations in human-like style for few-shot fine-grained image classification
Author: Li, Shenming; Feng, Lin; Xue, Linsong; Wang, Yifan; Wang, Dong

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 377-385. DOI: 10.1007/s13042-021-01473-8
2、Locality-constrained weighted collaborative-competitive representation for classification
Author: Gou, Jianping; Xiong, Xiangshuo; Wu, Hongwei; Du, Lan; Zeng, Shaoning; Yuan, Yunhao; Ou, Weihua

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 363-376. DOI: 10.1007/s13042-021-01461-y
3、Distance metric learning with local multiple kernel embedding
Author: Zhang, Qingshuo; Tsang, Eric C. C.; He, Qiang; Hu, Meng

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 1, pp. 79-92. DOI: 10.1007/s13042-021-01487-2
4、Micro-extended belief rule-based system with activation factor and parameter optimization for industrial cost prediction
Author: Wang, Suhui; Ye, Fei-Fei; Yang, Long-Hao; Liu, Jun; Wang, Hui; Martinez, Luis

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 1, pp. 63-78. DOI: 10.1007/s13042-021-01485-4
5、Small target deep convolution recognition algorithm based on improved YOLOv4
Author: Li, Fudong; Gao, Dongyang; Yang, Yuequan; Zhu, Junwu

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 387-394. DOI: 10.1007/s13042-021-01496-1
6、A hybrid-attention semantic segmentation network for remote sensing interpretation in land-use surveillance
Author: Lv, Ning; Zhang, Zenghui; Li, Cong; Deng, Jiaxuan; Su, Tao; Chen, Chen; Zhou, Yang

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 395-406. DOI: 10.1007/s13042-022-01517-7
7、Global attention network for collaborative saliency detection
Author: Li, Ce; Xuan, Shuxing; Liu, Fenghua; Chang, Enbing; Wu, Hailei

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 407-417. DOI: 10.1007/s13042-022-01531-9
8、An iterative recommendation model of supporting personalized learning based on schematic patterns mining from schema-enhanced contexts of problem-solving
Author: Guo, Lankun; Jia, Zhenhua; Ma, Guozhi; Li, Jinhai

Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 1, pp. 93-115. DOI: 10.1007/s13042-022-01525-7