12.180 37.16%

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IEEE Transactions on Neural Networks and Learning Systems - Journal Impact

The Journal Impact 2019-2020 of IEEE Transactions on Neural Networks and Learning Systems is 12.180, which is just updated in 2020. Compared with historical Journal Impact data, the Factor 2019 of IEEE Transactions on Neural Networks and Learning Systems grew by 37.16% . The Journal Impact Quartile of IEEE Transactions on Neural Networks and Learning Systems is Q1. The Journal Impact of an academic journal is a scientometric factor that reflects the yearly average number of citations that recent articles published in a given journal received. It is frequently used as a factor for the relative importance of a journal within its field; journals with higher Journal Impact are often deemed to be more important than those with lower ones. The Journal Impact measures the average number of citations received in a particular year (2019) by papers published in the journal during the two preceding years (2017-2018). Note that 2019 Journal Impact are reported in 2020; they cannot be calculated until all of the 2019 publications have been processed by the indexing agency. In addition to the 2-year Journal Impact, the 3-year Journal Impact can provide further insights and factors into the impact of IEEE Transactions on Neural Networks and Learning Systems.

13.5 ~ 14.0


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IEEE Transactions on Neural Networks and Learning Systems - Journal Impact Prediction System

100% scientists expect IEEE Transactions on Neural Networks and Learning Systems Journal Impact 2020 will be in the range of 13.5 ~ 14.0. Journal Impact Prediction System provides an open, transparent, and straightforward platform to help academic researchers Predict future factor and performance through the wisdom of crowds. Journal Impact Prediction System displays the exact community-driven factor without secret algorithms, hidden factors, or systematic delay.

IEEE Transactions on Neural Networks and Learning Systems Journal Impact Prediction System - Factor and Trend
  • Article Volume 2017 258
  • Article Volume 2016 230
  • Article Volume 2015 277
  • ISSN
  • 2162237X
  • Open Access
  • Publisher
  • IEEE Computational Intelligence Society
  • Country/Region
  • United States
  • History
  • Categories
  • Artificial Intelligence (Q1), Computer Networks and Communications (Q1), Computer Science Applications (Q1), Software (Q1)

IEEE Transactions on Neural Networks and Learning Systems - ISSN

The ISSN of IEEE Transactions on Neural Networks and Learning Systems is 2162237X. An ISSN is an 8-digit code used to identify newspapers, journals, magazines and periodicals of all kinds and on all media–print and electronic.

IEEE Transactions on Neural Networks and Learning Systems - ISSN

IEEE Transactions on Neural Networks and Learning Systems - Subscription (non-OA) Journal

IEEE Transactions on Neural Networks and Learning Systems is a Subscription-based (non-OA) Journal. Publishers own the rights to the articles in their journals. Anyone who wants to read the articles should pay by individual or institution to access the articles. Anyone who wants to use the articles in any way must obtain permission from the publishers.

IEEE Transactions on Neural Networks and Learning Systems - Open Access

IEEE Transactions on Neural Networks and Learning Systems - Publisher

IEEE Transactions on Neural Networks and Learning Systems is published by IEEE Computational Intelligence Society, which is located in the United States. The Publication History of IEEE Transactions on Neural Networks and Learning Systems covers 2012-ongoing.

IEEE Transactions on Neural Networks and Learning Systems - Publisher

IEEE Transactions on Neural Networks and Learning Systems - Categories

IEEE Transactions on Neural Networks and Learning Systems is a peer-reviewed scientific journal. The scope of IEEE Transactions on Neural Networks and Learning Systems covers Artificial Intelligence (Q1), Computer Networks and Communications (Q1), Computer Science Applications (Q1), Software (Q1).

IEEE Transactions on Neural Networks and Learning Systems - Categories

IEEE Transactions on Neural Networks and Learning Systems - Journal Factors

It is impossible to get a true picture of impact using a single factor alone, so a basket of factors is needed to support informed decisions. In addition to Abbreviation, Acceptance Rate, Review Speed, Research Hotspot and Template, several advanced Journal Factors including Citescore, H-Index, Self-Citation Ratio, SJR (SCImago Journal Rank Indicator) and SNIP (Source Normalized Impact per Paper) can provide you comprehensive insights into the IEEE Transactions on Neural Networks and Learning Systems.

IEEE Transactions on Neural Networks and Learning Systems - Journal Metrics

Journal Ranking