International Journal Of Machine Learning And Cybernetics SCIE

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

主要研究方向：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 非预警期刊审稿周期：

《国际机器学习与控制论杂志》(International Journal Of Machine Learning And Cybernetics)是一本由Springer Berlin Heidelberg出版的以COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE为研究特色的国际期刊，发表该领域相关的原创研究文章、评论文章和综述文章，及时报道该领域相关理论、实践和应用学科的最新发现，旨在促进该学科领域科学信息的快速交流。该期刊是一本未开放期刊，近三年没有被列入预警名单。

3区中科院分区
Q2 JCR分区
295 年发文量
3.1 IF影响因子
未开放 是否OA
30 H-index
2010 创刊年份
12 issues per year 出版周期
English 出版语言

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

[ 查看全部 ]

投稿咨询加急咨询

International Journal Of Machine Learning And Cybernetics期刊信息

ISSN：1868-8071
出版语言：English
是否OA：未开放
E-ISSN：1868-808X
出版地区：GERMANY
是否预警：否
出版商：Springer Berlin Heidelberg
出版周期：12 issues per year
创刊时间：2010
开源占比：0.037
Gold OA文章占比：3.75%
OA被引用占比：0.0215...
出版国人文章占比：0.56
出版撤稿占比：0
研究类文章占比：99.66%

International Journal Of Machine Learning And Cybernetics CiteScore评价数据（2024年最新版）

CiteScore

SJR

SNIP

CiteScore 指数

7.9

0.988

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%

名词解释：CiteScore 是衡量期刊所发表文献的平均受引用次数，是在 Scopus 中衡量期刊影响力的另一个指标。当年CiteScore 的计算依据是期刊最近4年（含计算年度）的被引次数除以该期刊近四年发表的文献数。例如，2022年的 CiteScore 计算方法为：2022年的 CiteScore =2019-2022年收到的对2019-2022年发表的文件的引用数量÷2019-2022年发布的文献数量注：文献类型包括：文章、评论、会议论文、书籍章节和数据论文。

International Journal Of Machine Learning And Cybernetics中科院评价数据

中科院 2023年12月升级版

Top期刊	综述期刊	大类学科		小类学科
否	否	计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

中科院 2022年12月升级版

Top期刊	综述期刊	大类学科		小类学科
否	否	计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

中科院 2021年12月旧的升级版

Top期刊	综述期刊	大类学科		小类学科
否	否	计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

中科院 2021年12月基础版

Top期刊	综述期刊	大类学科		小类学科
否	否	工程技术	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

中科院 2021年12月升级版

Top期刊	综述期刊	大类学科		小类学科
否	否	计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

中科院 2020年12月旧的升级版

Top期刊	综述期刊	大类学科		小类学科
否	否	计算机科学	3区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能	3区

International Journal Of Machine Learning And Cybernetics JCR评价数据（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%

International Journal Of Machine Learning And Cybernetics历年数据统计

影响因子

中科院分区

International Journal Of Machine Learning And Cybernetics中国学者发文选摘

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