Example of IEEE Transactions on Fuzzy Systems format
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Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format
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Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format Example of IEEE Transactions on Fuzzy Systems format
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IEEE Transactions on Fuzzy Systems — Template for authors

Publisher: IEEE
Categories Rank Trend in last 3 yrs
Control and Systems Engineering #2 of 260 down down by 1 rank
Applied Mathematics #4 of 548 -
Computational Theory and Mathematics #3 of 133 -
Artificial Intelligence #6 of 227 down down by 1 rank
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 931 Published Papers | 17049 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 27/06/2020
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Related Journals

open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 44.2
SJR: 3.811
SNIP: 11.215
open access Open Access

Wiley

Quality:  
Good
CiteRatio: 3.4
SJR: 0.365
SNIP: 0.9
open access Open Access
recommended Recommended

Taylor and Francis

Quality:  
High
CiteRatio: 6.8
SJR: 1.321
SNIP: 1.764

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

9.518

9% from 2018

Impact factor for IEEE Transactions on Fuzzy Systems from 2016 - 2019
Year Value
2019 9.518
2018 8.759
2017 8.415
2016 7.671
graph view Graph view
table view Table view

18.3

13% from 2019

CiteRatio for IEEE Transactions on Fuzzy Systems from 2016 - 2020
Year Value
2020 18.3
2019 16.2
2018 14.3
2017 16.1
2016 14.0
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 9% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 13% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

2.886

8% from 2019

SJR for IEEE Transactions on Fuzzy Systems from 2016 - 2020
Year Value
2020 2.886
2019 3.134
2018 2.794
2017 4.024
2016 3.408
graph view Graph view
table view Table view

3.548

11% from 2019

SNIP for IEEE Transactions on Fuzzy Systems from 2016 - 2020
Year Value
2020 3.548
2019 3.206
2018 3.421
2017 3.306
2016 3.188
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 8% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 11% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
IEEE Transactions on Fuzzy Systems

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IEEE

IEEE Transactions on Fuzzy Systems

The IEEE Transactions on Fuzzy Systems (TFS) is published quarterly. TFS will consider papers that deal with the theory, design or an application of fuzzy systems ranging from hardware to software. Authors are encouraged to submit articles, which disclose significant technical...... Read More

Engineering

i
Last updated on
27 Jun 2020
i
ISSN
1063-6706
i
Impact Factor
Very High - 4.443
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
IEEEtran
i
Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker, “Specular andreev reflection in graphene,” Phys. Rev. Lett., vol. 97, no. 6, p.

Top papers written in this journal

Journal Article DOI: 10.1109/91.493904
Fuzzy logic = computing with words
Lotfi A. Zadeh1

Abstract:

As its name suggests, computing with words (CW) is a methodology in which words are used in place of numbers for computing and reasoning. The point of this note is that fuzzy logic plays a pivotal role in CW and vice-versa. Thus, as an approximation, fuzzy logic may be equated to CW. There are two major imperatives for comput... As its name suggests, computing with words (CW) is a methodology in which words are used in place of numbers for computing and reasoning. The point of this note is that fuzzy logic plays a pivotal role in CW and vice-versa. Thus, as an approximation, fuzzy logic may be equated to CW. There are two major imperatives for computing with words. First, computing with words is a necessity when the available information is too imprecise to justify the use of numbers, and second, when there is a tolerance for imprecision which can be exploited to achieve tractability, robustness, low solution cost, and better rapport with reality. Exploitation of the tolerance for imprecision is an issue of central importance in CW. In CW, a word is viewed as a label of a granule; that is, a fuzzy set of points drawn together by similarity, with the fuzzy set playing the role of a fuzzy constraint on a variable. The premises are assumed to be expressed as propositions in a natural language. In coming years, computing with words is likely to evolve into a basic methodology in its own right with wide-ranging ramifications on both basic and applied levels. read more read less

Topics:

Fuzzy number (65%)65% related to the paper, Fuzzy set operations (63%)63% related to the paper, Perceptual computing (63%)63% related to the paper, Computing with words and perceptions (63%)63% related to the paper, Type-2 fuzzy sets and systems (62%)62% related to the paper
2,938 Citations
Journal Article DOI: 10.1109/91.481841
An approach to fuzzy control of nonlinear systems: stability and design issues
Hua O. Wang, Kazuo Tanaka1, M. Griffin

Abstract:

Presents a design methodology for stabilization of a class of nonlinear systems. First, the authors represent a nonlinear plant with a Takagi-Sugeno fuzzy model. Then a model-based fuzzy controller design utilizing the concept of the so-called "parallel distributed compensation" is employed. The main idea of the controller de... Presents a design methodology for stabilization of a class of nonlinear systems. First, the authors represent a nonlinear plant with a Takagi-Sugeno fuzzy model. Then a model-based fuzzy controller design utilizing the concept of the so-called "parallel distributed compensation" is employed. The main idea of the controller design is to derive each control rule so as to compensate each rule of a fuzzy system. The design procedure is conceptually simple and natural. Moreover, the stability analysis and control design problems can be reduced to linear matrix inequality (LMI) problems. Therefore, they can be solved efficiently in practice by convex programming techniques for LMIs. The design methodology is illustrated by application to the problem of balancing and swing-up of an inverted pendulum on a cart. read more read less

Topics:

Fuzzy control system (61%)61% related to the paper, Fuzzy logic (59%)59% related to the paper, Inverted pendulum (56%)56% related to the paper, Linear matrix inequality (56%)56% related to the paper, Convex optimization (53%)53% related to the paper
2,442 Citations
Journal Article DOI: 10.1109/TFUZZ.1993.390281
A fuzzy-logic-based approach to qualitative modeling

Abstract:

This paper discusses a general approach to quali- tative modeling based on fuzzy logic. The method of qualitative modeling is divided into two parts: fuzzy modeling and linguistic approximation. It proposes to use a fuzzy clustering method (fuzzy c-means method) to identify the structure of a fuzzy model. To clarify the advan... This paper discusses a general approach to quali- tative modeling based on fuzzy logic. The method of qualitative modeling is divided into two parts: fuzzy modeling and linguistic approximation. It proposes to use a fuzzy clustering method (fuzzy c-means method) to identify the structure of a fuzzy model. To clarify the advantages of the proposed method, it also shows some examples of modeling, among them a model of a dynamical process and a model of a human operator's control action. read more read less

Topics:

Fuzzy classification (71%)71% related to the paper, Fuzzy logic (70%)70% related to the paper, Neuro-fuzzy (67%)67% related to the paper, Fuzzy clustering (67%)67% related to the paper, Fuzzy associative matrix (66%)66% related to the paper
View PDF
2,394 Citations
Journal Article DOI: 10.1109/91.227387
A possibilistic approach to clustering
Raghu Krishnapuram1, James M. Keller1

Abstract:

The clustering problem is cast in the framework of possibility theory. The approach differs from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values can be interpreted as degrees of possibility of the points belonging to the cla... The clustering problem is cast in the framework of possibility theory. The approach differs from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values can be interpreted as degrees of possibility of the points belonging to the classes, i.e., the compatibilities of the points with the class prototypes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data is constructed, and the membership and prototype update equations are derived from necessary conditions for minimization of the criterion function. The advantages of the resulting family of possibilistic algorithms are illustrated by several examples. > read more read less

Topics:

Cluster analysis (56%)56% related to the paper, Fuzzy set (54%)54% related to the paper, Possibility theory (51%)51% related to the paper
View PDF
2,244 Citations
open accessOpen access Journal Article DOI: 10.1109/91.995115
Type-2 fuzzy sets made simple
Jerry M. Mendel1, Robert John2

Abstract:

Type-2 fuzzy sets let us model and minimize the effects of uncertainties in rule-base fuzzy logic systems. However, they are difficult to understand for a variety of reasons which we enunciate. In this paper, we strive to overcome the difficulties by: (1) establishing a small set of terms that let us easily communicate about ... Type-2 fuzzy sets let us model and minimize the effects of uncertainties in rule-base fuzzy logic systems. However, they are difficult to understand for a variety of reasons which we enunciate. In this paper, we strive to overcome the difficulties by: (1) establishing a small set of terms that let us easily communicate about type-2 fuzzy sets and also let us define such sets very precisely, (2) presenting a new representation for type-2 fuzzy sets, and (3) using this new representation to derive formulas for union, intersection and complement of type-2 fuzzy sets without having to use the Extension Principle. read more read less

Topics:

Type-2 fuzzy sets and systems (74%)74% related to the paper, Fuzzy set operations (72%)72% related to the paper, Defuzzification (69%)69% related to the paper, Fuzzy set (68%)68% related to the paper, Fuzzy number (68%)68% related to the paper
View PDF
2,192 Citations
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Frequently asked questions

1. Can I write IEEE Transactions on Fuzzy Systems in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the IEEE Transactions on Fuzzy Systems guidelines and auto format it.

2. Do you follow the IEEE Transactions on Fuzzy Systems guidelines?

Yes, the template is compliant with the IEEE Transactions on Fuzzy Systems guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in IEEE Transactions on Fuzzy Systems?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the IEEE Transactions on Fuzzy Systems citation style.

4. Can I use the IEEE Transactions on Fuzzy Systems templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for IEEE Transactions on Fuzzy Systems.

5. Can I use a manuscript in IEEE Transactions on Fuzzy Systems that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper IEEE Transactions on Fuzzy Systems that you can download at the end.

6. How long does it usually take you to format my papers in IEEE Transactions on Fuzzy Systems?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in IEEE Transactions on Fuzzy Systems.

7. Where can I find the template for the IEEE Transactions on Fuzzy Systems?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Transactions on Fuzzy Systems's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the IEEE Transactions on Fuzzy Systems's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. IEEE Transactions on Fuzzy Systems an online tool or is there a desktop version?

SciSpace's IEEE Transactions on Fuzzy Systems is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

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11. What is the output that I would get after using IEEE Transactions on Fuzzy Systems?

After writing your paper autoformatting in IEEE Transactions on Fuzzy Systems, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is IEEE Transactions on Fuzzy Systems's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for IEEE Transactions on Fuzzy Systems?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for IEEE Transactions on Fuzzy Systems. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In IEEE Transactions on Fuzzy Systems?

The 5 most common citation types in order of usage for IEEE Transactions on Fuzzy Systems are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the IEEE Transactions on Fuzzy Systems?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Transactions on Fuzzy Systems's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download IEEE Transactions on Fuzzy Systems in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in IEEE Transactions on Fuzzy Systems Endnote style according to Elsevier guidelines.

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