IEEE Transactions on Neural Networks and Learning Systems- Impact Score, Ranking, SJR, h-index, Citescore, Rating, Publisher, ISSN, and Other Important Details

About IEEE Transactions on Neural Networks and Learning Systems

IEEE Transactions on Neural Networks and Learning Systems is a journal published by IEEE Computational Intelligence Society. This journal covers the area[s] related to Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Software, etc. The coverage history of this journal is as follows: 2012-2022. The rank of this journal is 483. This journal's impact score, h-index, and SJR are 11.06, 234, and 3.447, respectively. The ISSN of this journal is/are as follows: 2162237X, 21622388.

The best quartile of IEEE Transactions on Neural Networks and Learning Systems is Q1. This journal has received a total of 19156 citations during the last three years (Preceding 2022).

IEEE Transactions on Neural Networks and Learning Systems Impact Score 2022-2023

The latest impact score (IS) of the IEEE Transactions on Neural Networks and Learning Systems is 11.06. It is computed in the year 2023 as per its definition and based on Scopus data. 11.06

It is increased by a factor of around 0.01, and the percentage change is 0.09% compared to the preceding year 2021, indicating a rising trend.

The impact score (IS), also denoted as the 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.

Prediction of IEEE Transactions on Neural Networks and Learning Systems Impact Score 2023

Impact Score 2022 of IEEE Transactions on Neural Networks and Learning Systems is 11.06. If a similar upward trend continues, IS may increase in 2023 as well.

IEEE Transactions on Neural Networks and Learning Systems h-index

 

The h-index of IEEE Transactions on Neural Networks and Learning Systems is 234. By definition of the h-index, this journal has at least 234 published articles with more than 234 citations.

What is h-index?

The h-index (also known as the Hirsch index or Hirsh index) is a scientometric parameter used to evaluate the scientific impact of the publications and journals. It is defined as the maximum value of h such that the given Journal has published at least h papers and each has at least h citations.

IEEE Transactions on Neural Networks and Learning Systems ISSN

The International Standard Serial Number (ISSN) of IEEE Transactions on Neural Networks and Learning Systems is/are as follows: 2162237X, 21622388.

The ISSN is a unique 8-digit identifier for a specific publication like Magazine or Journal. The ISSN is used in the postal system and in the publishing world to identify the articles that are published in journals, magazines, newsletters, etc. This is the number assigned to your article by the publisher, and it is the one you will use to reference your article within the library catalogues.

ISSN code (also called as "ISSN structure" or "ISSN syntax") can be expressed as follows: NNNN-NNNC
Here, N is in the set {0,1,2,3...,9}, a digit character, and C is in {0,1,2,3,...,9,X}

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

The IEEE Transactions on Neural Networks and Learning Systems is ranked 483 among 27955 Journals, Conferences, and Book Series. As per SJR, this journal is ranked 3.447.

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.

IEEE Transactions on Neural Networks and Learning Systems Publisher

The publisher of IEEE Transactions on Neural Networks and Learning Systems is IEEE Computational Intelligence Society. The publishing house of this journal is located in the United States. Its coverage history is as follows: 2012-2022.

Call For Papers (CFPs)

Please check the official website of this journal to find out the complete details and Call For Papers (CFPs).

Abbreviation

The International Organization for Standardization 4 (ISO 4) abbreviation of IEEE Transactions on Neural Networks and Learning Systems is IEEE Trans. Neural Netw. Learn. Syst.. ISO 4 is an international standard which defines a uniform and consistent system for the abbreviation of serial publication titles, which are published regularly. The primary use of ISO 4 is to abbreviate or shorten the names of scientific journals using the technique of List of Title Word Abbreviations (LTWA).

As ISO 4 is an international standard, the abbreviation ('IEEE Trans. Neural Netw. Learn. Syst.') can be used for citing, indexing, abstraction, and referencing purposes.

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

If your area of research or discipline is related to Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Software, etc., please check the journal's official website to understand the complete publication process.

Acceptance Rate

There are several factors that influence the acceptance rate of any academic journal. Here are some critical parameters that are considered while calculating the acceptance rate:

• Interest/demand of researchers/scientists for publishing in a specific journal/conference.
• The complexity of the peer review process and timeline.
• Time taken from draft submission to final publication.
• Number of submissions received and acceptance slots
• And Many More.

The simplest way to find out the acceptance rate or rejection rate of a Journal/Conference is to check with the journal's/conference's editorial team through emails or through the official website.

Credits and Sources

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