| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 563 | 36 | 42 | 10 |
| Mathematics | 590 | 10 | 23 | 4 |
The objective of the journal is to combine knowledge in the areas of Fuzzy logic, Artificial intelligence, Fuzzy number, Discrete mathematics and Mathematical optimization. The studies on Fuzzy logic discussed can also contribute to research in the domains of Algorithm and Data mining. Most of the works presented in it deals with Data mining but it intersects with the subject of Cluster analysis.
Artificial intelligence research featured in it incorporates concerns from various other topics such as Machine learning, Theoretical computer science, Set (abstract data type) and Pattern recognition. In addition to Fuzzy number research, the journal aims to explore topics under Fuzzy set operations, Fuzzy classification and Membership function. Type-2 fuzzy sets and systems is a key component of Fuzzy set operations research discussed in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems.
Fuzzy classification study tackled is connected to the field of Neuro-fuzzy. Issues in Discrete mathematics were discussed, taking into consideration concepts from other disciplines like Applied mathematics, Pure mathematics and Algebra. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems dives deep in exploring the relationship between the study of Defuzzification and Fuzzy associative matrix.
The most cited papers investigate areas of study like Fuzzy logic, Fuzzy number, Artificial intelligence, Mathematical optimization and Discrete mathematics. The journal articles explore topics in Fuzzy logic which can be helpful for research in disciplines like Expression (mathematics), Algebra and Data mining. The journal publications address concerns in Fuzzy number which are intertwined with other disciplines, such as Fuzzy set operations and Fuzzy classification.
The aim of International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems is to expand the discussion of research in Fuzzy logic, Artificial intelligence, Mathematical optimization, Control theory and Algorithm. Fuzzy number research are fields of study within Fuzzy logic but they also intertwine with concepts in Lagrangian. The research on Artificial intelligence featured in it combines topics in other fields like Machine learning, Upload, Computer vision and Pattern recognition.
The journal facilitates discussions on Mathematical optimization that incorporate concepts from other fields like Fuzzy optimal control, Expected value, Bi level programming and Fuzzy programming. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems features works in Control theory, more specifically Markov jump, Extended Kalman filter and Kalman filter, and explores their relation to disciplines like Cost control. Topics in Algorithm were tackled in line with various other fields like Kernel (statistics), High-dimensional model representation, Structural system, Support vector machine and Bounded function.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 13.04% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 22.50% were posted by at least one author from the top 10 institutions publishing in the journal. Another 2.50% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 75.00% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Zhaoxia Wang;Seng-Beng Ho;Erik Cambria
(2020)Umesh Gupta;Deepak Gupta
(2021)Dharmadas Mardanya;Gurupada Maity;Sankar Kumar Roy
(2021)Sujatha Krishnamoorthy;A. Shanthini;Gunasekaran Manogaran;Gunasekaran Manogaran;Vijayalakshmi Saravanan
(2021)Arathi Reghukumar;L. Jani Anbarasi;J. Prassanna;Ramachandran Manikandan
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