International Journal of Machine Learning and Cybernetics

Journal website Submission website

Note: The following journal information is for reference only. Please check the journal website for updated information prior to submission.

Journal Title

INT J MACH LEARN CYB

ISSN / eISSN

1868-8071 / 1868-808X

Aims and Scope

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

Subject Area

COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

CiteScore

8.50

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CiteScore Ranking

Category	Quartile	Rank
Computer Science - Software	Q1	#70/404
Computer Science - Computer Vision and Pattern Recognition	Q1	#18/100
Computer Science - Artificial Intelligence	Q1	#64/301

Web of Science Core Collection

Science Citation Index Expanded (SCIE)	Social Sciences Citation Index (SSCI)
Indexed	-

Category (Journal Citation Reports 2023)	Quartile
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE - SCIE	Q2

H-index

Country/Area of Publication

GERMANY

Publisher

Springer Berlin Heidelberg

Publication Frequency

12 issues per year

Year Publication Started

2010

Annual Article Volume

272

Open Access

Contact

TIERGARTENSTRASSE 17, HEIDELBERG, GERMANY, D-69121

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Verified Reviews

Note: Verified reviews are sourced from across review platforms and social media globally.

The latest data shows that the International Journal of Machine Learning and Cybernetics receives over 1000 submissions per year, with around 170 articles published annually. The acceptance rate is less than 20% (referring to the average acceptance rate, as different topics may have varying levels of difficulty in acceptance). Generally, the first review process takes 3 months, and if a new reviewer is needed (if most of the initial reviewers reject the submission), it takes 5 months for the first review. The first review comments will be received within 9 months at the latest (if there is no news after 6 months, you can send an email to the editor-in-chief for a reminder, and they usually respond quickly). Typically, the processing of an article is completed within 12 months (regardless of whether the paper is accepted or not). We hope this information is useful to everyone.

2021-05-31

Posted on October 18, 2020, received first-round comments on February 4, 2021, the first review was quite fast. There were a total of two reviewers, the first reviewer provided some revision suggestions, and the other reviewer expressed their opinion on the novelty of the paper. In addition, I provided a code link in the abstract, but it was not uploaded completely at the time, and the second reviewer also pointed out the incomplete code. Finally, the editor-in-chief rejected it. It has now been resubmitted.

2021-03-30

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