Example of International Journal of Fuzzy Systems format
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Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format
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Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format Example of International Journal of Fuzzy Systems format
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International Journal of Fuzzy Systems — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Computational Theory and Mathematics #13 of 133 up up by 20 ranks
Theoretical Computer Science #14 of 120 up up by 25 ranks
Software #66 of 389 up up by 96 ranks
Artificial Intelligence #45 of 227 up up by 30 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 719 Published Papers | 5273 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 30/06/2020
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Related Journals

open access Open Access

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Quality:  
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CiteRatio: 3.5
SJR: 0.685
SNIP: 1.383
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Quality:  
High
CiteRatio: 5.0
SJR: 0.624
SNIP: 1.866

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.

4.406

43% from 2018

Impact factor for International Journal of Fuzzy Systems from 2016 - 2019
Year Value
2019 4.406
2018 3.085
2017 2.396
2016 2.198
graph view Graph view
table view Table view

7.3

26% from 2019

CiteRatio for International Journal of Fuzzy Systems from 2016 - 2020
Year Value
2020 7.3
2019 5.8
2018 4.2
2017 3.0
2016 2.4
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 43% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 26% 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.

0.73

4% from 2019

SJR for International Journal of Fuzzy Systems from 2016 - 2020
Year Value
2020 0.73
2019 0.758
2018 0.514
2017 0.47
2016 0.682
graph view Graph view
table view Table view

1.279

11% from 2019

SNIP for International Journal of Fuzzy Systems from 2016 - 2020
Year Value
2020 1.279
2019 1.436
2018 1.025
2017 1.037
2016 1.154
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 4% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 11% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

International Journal of Fuzzy Systems

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Springer

International Journal of Fuzzy Systems

Approved by publishing and review experts on SciSpace, this template is built as per for International Journal of Fuzzy Systems formatting guidelines as mentioned in Springer author instructions. The current version was created on and has been used by 988 authors to write and format their manuscripts to this journal.

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Last updated on
30 Jun 2020
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ISSN
2199-3211
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Open Access
Hybrid
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Citation Type
Numbered
[25]
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Bibliography Example
Blonder, G.E., Tinkham, M., Klapwijk, T.M.: Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B 25(7), 4515–4532 (1982). URL 10.1103/PhysRevB.25.4515

Top papers written in this journal

Journal Article DOI: 10.1007/S40815-017-0401-3
Survey on Fuzzy-Logic-Based Guidance and Control of Marine Surface Vehicles and Underwater Vehicles
Xianbo Xiang1, Caoyang Yu1, Lionel Lapierre, Jialei Zhang1, Qin Zhang1

Abstract:

Fuzzy logic control, due to its simple control structure, easy and cost-effective design, has been successfully employed to the application of guidance and control in robotic fields. This paper aims to review fuzzy-logic-based guidance and control in an important branch of robots—marine robotic vehicles. First, guidance and m... Fuzzy logic control, due to its simple control structure, easy and cost-effective design, has been successfully employed to the application of guidance and control in robotic fields. This paper aims to review fuzzy-logic-based guidance and control in an important branch of robots—marine robotic vehicles. First, guidance and motion forms including the maneuvering, path following, trajectory tracking, and position stabilization are described. Subsequently, the application of three major classes of fuzzy logic control, including the conventional fuzzy control (Mamdani fuzzy control and Takagi–Sugeno–Kang fuzzy control), adaptive fuzzy control (self-tuning fuzzy control and direct/indirect adaptive fuzzy control), and hybrid fuzzy control (fuzzy PID control, fuzzy sliding mode control, and neuro-fuzzy control) are presented. In particular, we summarize the design and analysis process of direct/indirect adaptive fuzzy control and fuzzy PID control in marine robotic fields. In addition, two comparative results between hybrid fuzzy control and the corresponding single control are provided to illustrate the superiority of hybrid fuzzy control. Finally, trends of the fuzzy future in marine robotic vehicles are concluded based on its state of the art. read more read less

Topics:

Fuzzy control system (71%)71% related to the paper, Fuzzy logic (70%)70% related to the paper, Computational intelligence (52%)52% related to the paper
263 Citations
Journal Article DOI: 10.1007/S40815-017-0432-9
Hesitant Fuzzy Linguistic Term Set and Its Application in Decision Making: A State-of-the-Art Survey

Abstract:

The hesitant fuzzy linguistic term set (HFLTS) has gained great success as it can be used to represent several linguistic terms or comparative linguistic expressions together with some context-free grammars. This new approach has enabled the analysis and computing of linguistic expressions with uncertainties and opened the do... The hesitant fuzzy linguistic term set (HFLTS) has gained great success as it can be used to represent several linguistic terms or comparative linguistic expressions together with some context-free grammars. This new approach has enabled the analysis and computing of linguistic expressions with uncertainties and opened the door for the possibility to develop more comprehensive and powerful decision theories and methods based on linguistic knowledge. Lots of new approaches and proposals for decision-making problems have been proposed to overcome the limitations of previous linguistic decision-making approaches. Now and in the future, decision-making methodologies and algorithms with hesitant fuzzy linguistic models would be a quite promising research line representing a high-quality breakthrough in this topic. To facilitate the study on HFLTS theory, this paper makes a state-of-the-art survey on HFLTSs based on the 134 selected papers from Web of Sciences published from January 2012 to October 2017. We justify the motivation, definitions, operations, comparison methods and measures of HFLTSs. We also summarize the different extensions of HFLTSs. The studies on multiple criteria decision making (MCDM) with HFLTSs in terms of aggregation operators and MCDM methods are clearly reviewed. We also conduce some overviews on decision making with hesitant fuzzy linguistic preference relations. The applications, research challenges and future directions are also given. read more read less

Topics:

Multiple-criteria decision analysis (52%)52% related to the paper
209 Citations
Journal Article DOI: 10.1007/S40815-017-0400-4
Evidential Supplier Selection Based on DEMATEL and Game Theory
Tianyu Liu1, Tianyu Liu2, Yong Deng2, Yong Deng1, Yong Deng3, Felix T.S. Chan4

Abstract:

The supplier selection plays an important role in supplier chain management. How to evaluate the performance of suppliers is still an open issue. Multi-criteria decision-making (MCDM), due to its ability of solving multi-source information problem, has become a quite effective tool. Currently, the analytic network process (AN... The supplier selection plays an important role in supplier chain management. How to evaluate the performance of suppliers is still an open issue. Multi-criteria decision-making (MCDM), due to its ability of solving multi-source information problem, has become a quite effective tool. Currently, the analytic network process (ANP) and Entropy weight are employed to solved MCDM problems. However, these techniques ignore the one-sidedness of the single weighting method and cannot deal with the uncertainties of input data. In this paper, a new evidential ANP methodology based on game theory is proposed to efficiently address supplier management under uncertain environment. First, ANP and entropy weight are employed to obtain the subjective and objective weights of criteria. Second, based on decision-making trial and evaluation laboratory (DEMATEL) and game theory, the comprehensive weight of ANP and entropy weight can be determined. Game theory is employed to combine the merits of subjective weight and objective weight, and DEMATEL is adopted to adjust the weight of criteria to make the result more reasonable. Finally, evidence theory is adopted to deal with the uncertainties of input data and get the supplier selection result. A case study is given to demonstrate the proposed modeling process. By comparing with the existing methods, we demonstrate that the proposed model has many advantages and it shows the efficiency and rationality in supplier selection problem. read more read less

Topics:

Supplier relationship management (59%)59% related to the paper, Analytic network process (54%)54% related to the paper, Game theory (52%)52% related to the paper, Multiple-criteria decision analysis (51%)51% related to the paper, Weighting (51%)51% related to the paper
188 Citations
Journal Article DOI: 10.1007/S40815-017-0338-6
Bipolar Fuzzy Hamacher Aggregation Operators in Multiple Attribute Decision Making
Guiwu Wei1, Guiwu Wei2, Fuad E. Alsaadi1, Tasawar Hayat1, Tasawar Hayat3, Ahmed Alsaedi1

Abstract:

In this paper, we have investigated the multiple attribute decision-making problems with bipolar fuzzy information. Motivated by the Hamacher operations, we have proposed bipolar fuzzy Hamacher weighted average operator, bipolar fuzzy Hamacher ordered weighted average operator, bipolar fuzzy Hamacher hybrid average operator, ... In this paper, we have investigated the multiple attribute decision-making problems with bipolar fuzzy information. Motivated by the Hamacher operations, we have proposed bipolar fuzzy Hamacher weighted average operator, bipolar fuzzy Hamacher ordered weighted average operator, bipolar fuzzy Hamacher hybrid average operator, bipolar fuzzy Hamacher weighted geometric operator, bipolar fuzzy Hamacher ordered weighted geometric operator, bipolar fuzzy Hamacher hybrid geometric operator. We investigate the characteristics and special cases of these operators. Then, we have utilized these operators to develop some approaches to solve the bipolar fuzzy multiple attribute decision-making problems. Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness. read more read less

Topics:

Fuzzy logic (56%)56% related to the paper, Operator (computer programming) (51%)51% related to the paper
183 Citations
Journal Article DOI: 10.1007/S40815-017-0313-2
Decision Making with Uncertainty Using Hesitant Fuzzy Sets
Shahzad Faizi1, Tabasam Rashid1, Wojciech Sałabun2, Sohail Zafar1, Jarosław Wątróbski2

Abstract:

Actual existing multi-criteria decision-making (MCDM) methods yield results that may be questionable and unreliable. These methods very often ignore the issue of uncertainty and rank reversal paradox, which are fundamental and important challenges of MCDM methods. In response to these challenges, the Characteristic Objects Me... Actual existing multi-criteria decision-making (MCDM) methods yield results that may be questionable and unreliable. These methods very often ignore the issue of uncertainty and rank reversal paradox, which are fundamental and important challenges of MCDM methods. In response to these challenges, the Characteristic Objects Method (COMET) was developed. Despite it being immune to the rank reversal paradox, classical COMET is not designed for uncertain, decisional problems. In this paper, we propose to extend COMET using hesitant fuzzy set (HFS) theory. Hesitant fuzzy set theory is a powerful tool to express the uncertainty that derives from an expert comparing characteristic objects and identifying membership functions for each criterion domain. We present the theoretical foundations and principles of COMET, and we provide an illustrative example to show how COMET handles uncertain decision problems both practically and effectively. read more read less

Topics:

Type-2 fuzzy sets and systems (60%)60% related to the paper, Fuzzy set (56%)56% related to the paper, Rank reversals in decision-making (56%)56% related to the paper, Decision problem (52%)52% related to the paper, Comet (programming language) (51%)51% related to the paper
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164 Citations
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Frequently asked questions

1. Can I write International Journal of 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 International Journal of Fuzzy Systems guidelines and auto format it.

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5. Can I use a manuscript in International Journal of 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 International Journal of Fuzzy Systems that you can download at the end.

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12. Is International Journal of 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 International Journal of 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 International Journal of 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 International Journal of Fuzzy Systems?

The 5 most common citation types in order of usage for International Journal of Fuzzy Systems are:.

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

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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 International Journal of Fuzzy Systems Endnote style according to Elsevier guidelines.

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