IEEE Transactions on Neural Networks and Learning Systems

Impact, Factor and Metrics, Impact Score, Ranking, h-index, SJR, Rating, Publisher, ISSN, and More

Aim and Scope

IEEE Transactions on Neural Networks and Learning Systems publishes technical articles that deal with the theory, design, and applications of neural networks and related learning systems. Emphasis will be given to artificial neural networks and learning systems.

About IEEE Transactions on Neural Networks and Learning Systems

IEEE Transactions on Neural Networks and Learning Systems is a journal covering the technologies/fields/categories related to Artificial Intelligence (Q1); Computer Networks and Communications (Q1); Computer Science Applications (Q1); Software (Q1). It is published by IEEE Computational Intelligence Society. The overall rank of IEEE Transactions on Neural Networks and Learning Systems is 389. According to SCImago Journal Rank (SJR), this journal is ranked 4.17. SCImago Journal Rank is an indicator, which measures the scientific influence of journals. It considers the number of citations received by a journal and the importance of the journals from where these citations come. SJR acts as an alternative to the Journal Impact Factor (or an average number of citations received in last 2 years). This journal has an h-index of 251. The best quartile for this journal is Q1.

The ISSN of IEEE Transactions on Neural Networks and Learning Systems journal is 2162237X, 21622388. An International Standard Serial Number (ISSN) is a unique code of 8 digits. It is used for the recognition of journals, newspapers, periodicals, and magazines in all kind of forms, be it print-media or electronic. IEEE Transactions on Neural Networks and Learning Systems is cited by a total of 23364 articles during the last 3 years (Preceding 2023).

IEEE Transactions on Neural Networks and Learning Systems Impact IF 2023-2024

The Impact IF 2023 of IEEE Transactions on Neural Networks and Learning Systems is 11.83, which is computed in 2024 as per its definition. IEEE Transactions on Neural Networks and Learning Systems IF is increased by a factor of 0.77 and approximate percentage change is 6.96% when compared to preceding year 2022, which shows a rising trend. The impact IF, also denoted as Journal impact score (JIS), of an academic journal is a measure of the yearly average number of citations to recent articles published in that journal. It is based on Scopus data.

IEEE Transactions on Neural Networks and Learning Systems Impact IF 2024 Prediction

Impact IF 2023 of IEEE Transactions on Neural Networks and Learning Systems is 11.83. If the same upward trend persists, Impact IF may rise in 2024 as well.

IEEE Transactions on Neural Networks and Learning Systems h-index

 

IEEE Transactions on Neural Networks and Learning Systems has an h-index of 251. It means 251 articles of this journal have more than 251 number of citations. The h-index is a way of measuring the productivity and citation impact of the publications. The h-index is defined as the maximum value of h such that the given journal/author has published h papers that have each been cited at least h number of times.

IEEE Transactions on Neural Networks and Learning Systems ISSN

The ISSN of IEEE Transactions on Neural Networks and Learning Systems is 2162237X, 21622388. ISSN stands for International Standard Serial Number.

An ISSN is a unique code of 8 digits. It is used for the recognition of journals, newspapers, periodicals, and magazines in all kind of forms, be it print-media or electronic.

IEEE Transactions on Neural Networks and Learning Systems Rank and SCImago Journal Rank (SJR)

The overall rank of IEEE Transactions on Neural Networks and Learning Systems is 389. According to SCImago Journal Rank (SJR), this journal is ranked 4.17. SCImago Journal Rank is an indicator, which measures the scientific influence of journals. It considers the number of citations received by a journal and the importance of the journals from where these citations come.

SJR of IEEE Transactions on Neural Networks and Learning Systems by Year

Ranking of IEEE Transactions on Neural Networks and Learning Systems by Year

IEEE Transactions on Neural Networks and Learning Systems Publisher

IEEE Transactions on Neural Networks and Learning Systems is published by IEEE Computational Intelligence Society. It's publishing house is located in United States. Coverage history of this journal is as following: 2012-2023. The organization or individual who handles the printing and distribution of printed or digital publications is known as Publisher.

Call For Papers

Visit the official website of the journal/conference to check the further details about the call for papers.

Abbreviation

The IS0 4 standard abbreviation of IEEE Transactions on Neural Networks and Learning Systems is IEEE Trans. Neural Netw. Learn. Syst.. This abbreviation ('IEEE Trans. Neural Netw. Learn. Syst.') is well recommended and approved for the purpose of indexing, abstraction, referencing and citing goals. It meets all the essential criteria of ISO 4 standard.

ISO 4 (International Organization for Standardization 4) is an international standard that defines a uniform and consistent system for abbreviating serial publication titles and journals.

How to publish in IEEE Transactions on Neural Networks and Learning Systems

If your research field is/are related to Artificial Intelligence (Q1); Computer Networks and Communications (Q1); Computer Science Applications (Q1); Software (Q1), then please visit the official website of this journal.

Acceptance Rate

The acceptance rate/percentage of any academic journal/conference depends upon many parameters. Some of the critical parameters are listed below.

• The demand or interest of researchers/scientists in publishing in a specific Journal/Conference.
• Peer review complexity and timeline.
• The mix of unsolicited and invited submissions.
• The time it takes from manuscript submission to final publication.
• And Many More.

It is essential to understand that the acceptance rate/rejection rate of papers varies among journals. Some Journals considers all the manuscripts submissions as a basis of acceptance rate computation. On the other hand, few consider the only manuscripts sent for peer review or few even not bother about the accurate maintenance of total submissions. Hence, it can provide a rough estimation only.

The best way to find out the acceptance rate is to reach out to the associated editor or to check the official website of the Journal/Conference.

Credits and Sources

• Scimago Journal & Country Rank (SJR), https://www.scimagojr.com/
• Journal Impact Factor, https://clarivate.com/
• IEEE Transactions on Neural Networks and Learning Systems Official Website
• IEEE Transactions on Neural Networks and Learning Systems Wikipedia