International Journal Of Machine Learning And Cybernetics SCIE

國際簡稱：INT J MACH LEARN CYB 參考譯名：國際機器學習與控制論雜志

主要研究方向：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 非預警期刊審稿周期：

《國際機器學習與控制論雜志》(International Journal Of Machine Learning And Cybernetics)是一本由Springer Berlin Heidelberg出版的以COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE為研究特色的國際期刊，發表該領域相關的原創研究文章、評論文章和綜述文章，及時報道該領域相關理論、實踐和應用學科的最新發現，旨在促進該學科領域科學信息的快速交流。該期刊是一本未開放期刊，近三年沒有被列入預警名單。

3區中科院分區
Q2 JCR分區
295 年發文量
3.1 IF影響因子
未開放 是否OA
30 H-index
2010 創刊年份
12 issues per year 出版周期
English 出版語言

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

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International Journal Of Machine Learning And Cybernetics期刊信息

ISSN：1868-8071
出版語言：English
是否OA：未開放
E-ISSN：1868-808X
出版地區：GERMANY
是否預警：否
出版商：Springer Berlin Heidelberg
出版周期：12 issues per year
創刊時間：2010
開源占比：0.037
Gold OA文章占比：3.75%
OA被引用占比：0.0215...
出版國人文章占比：0.56
出版撤稿占比：0
研究類文章占比：99.66%

International Journal Of Machine Learning And Cybernetics CiteScore評價數據（2024年最新版）

CiteScore

SJR

SNIP

CiteScore 指數

7.9

0.988

1.217

學科類別	分區	排名	百分位
大類：Computer Science 小類：Computer Vision and Pattern Recognition	Q1	21 / 106	80%
大類：Computer Science 小類：Software	Q1	85 / 407	79%
大類：Computer Science 小類：Artificial Intelligence	Q1	84 / 350	76%

名詞解釋：CiteScore 是衡量期刊所發表文獻的平均受引用次數，是在 Scopus 中衡量期刊影響力的另一個指標。當年CiteScore 的計算依據是期刊最近4年（含計算年度）的被引次數除以該期刊近四年發表的文獻數。例如，2022年的 CiteScore 計算方法為：2022年的 CiteScore =2019-2022年收到的對2019-2022年發表的文件的引用數量÷2019-2022年發布的文獻數量注：文獻類型包括：文章、評論、會議論文、書籍章節和數據論文。

International Journal Of Machine Learning And Cybernetics中科院評價數據

中科院 2023年12月升級版

Top期刊	綜述期刊	大類學科		小類學科
否	否	計算機科學	3區	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機：人工智能	3區

中科院 2022年12月升級版

Top期刊	綜述期刊	大類學科		小類學科
否	否	計算機科學	3區	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機：人工智能	3區

中科院 2021年12月舊的升級版

Top期刊	綜述期刊	大類學科		小類學科
否	否	計算機科學	3區	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機：人工智能	3區

中科院 2021年12月基礎版

Top期刊	綜述期刊	大類學科		小類學科
否	否	工程技術	3區	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機：人工智能	3區

中科院 2021年12月升級版

Top期刊	綜述期刊	大類學科		小類學科
否	否	計算機科學	3區	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機：人工智能	3區

中科院 2020年12月舊的升級版

Top期刊	綜述期刊	大類學科		小類學科
否	否	計算機科學	3區	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機：人工智能	3區

International Journal Of Machine Learning And Cybernetics JCR評價數據（2023-2024年最新版）

按JIF指標學科分區	收錄子集	分區	排名	百分位
學科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	86 / 197	56.6%

按JCI指標學科分區	收錄子集	分區	排名	百分位
學科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	84 / 198	57.83%

International Journal Of Machine Learning And Cybernetics歷年數據統計

影響因子

中科院分區

International Journal Of Machine Learning And Cybernetics中國學者發文選摘

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