Symmetry in Fuzzy Sets and Systems

A special issue of Symmetry (ISSN 2073-8994).

Deadline for manuscript submissions: closed (30 November 2017) | Viewed by 18646

Special Issue Editor

INESC-ID/Instituto Superior Técnico, Universidade de Lisboa, R. Alves Redol, 9, 1000-029 Lisboa, Portugal
Interests: computational intelligence; intelligent systems; fuzzy sets; social networks datamining; text mining; signal processing

Special Issue Information

Dear Colleagues,

Symmetry is, and has generally been, present in many, if not most, works involving Fuzzy sets and Fuzzy systems. Whenever a human is involved in the design of a fuzzy system, they naturally tend to opt for symmetric features. The most common examples are the fuzzy membership functions and linguistic terms, often designed symmetrically and regularly-distributed over the universe of discourse. However, this does not usually happen if features are automatically generated. The same is true for many other aspects of fuzzy theory and applications, from fuzzy measures to fuzzy control.

In this Special Issue of Symmetry we will focus on the reasons and consequences for the prevalent use of symmetry in many topics, such as fuzzy measures, fuzzy relations, fuzzy control, fuzzy clustering, fuzzy decision analysis, fuzzy modeling, fuzzy information retrieval, fuzzy cognitive maps, etc. Applications and/or fuzzy theory works, where symmetry, or the deliberate lack of symmetry, is present, are also welcome.

Prof. Dr. João Paulo Carvalho
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • symmetry
  • fuzzy sets
  • fuzzy logic
  • fuzzy systems
  • fuzzy theory
  • fuzzy applications

Published Papers (5 papers)

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Research

20 pages, 4234 KiB  
Article
Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products
by Nazario Garcia, Javier Puente, Isabel Fernandez and Paolo Priore
Symmetry 2018, 10(1), 22; https://doi.org/10.3390/sym10010022 - 10 Jan 2018
Cited by 7 | Viewed by 4196
Abstract
This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: [...] Read more.
This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method’s superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process. Full article
(This article belongs to the Special Issue Symmetry in Fuzzy Sets and Systems)
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5095 KiB  
Article
Time Series Seasonal Analysis Based on Fuzzy Transforms
by Ferdinando Di Martino and Salvatore Sessa
Symmetry 2017, 9(11), 281; https://doi.org/10.3390/sym9110281 - 17 Nov 2017
Cited by 6 | Viewed by 3455
Abstract
We define a new seasonal forecasting method based on fuzzy transforms. We use the best interpolating polynomial for extracting the trend of the time series and generate the inverse fuzzy transform on each seasonal subset of the universe of discourse for predicting the [...] Read more.
We define a new seasonal forecasting method based on fuzzy transforms. We use the best interpolating polynomial for extracting the trend of the time series and generate the inverse fuzzy transform on each seasonal subset of the universe of discourse for predicting the value of an assigned output. In the first example, we use the daily weather dataset of the municipality of Naples (Italy) starting from data collected from 2003 to 2015 making predictions on mean temperature, max temperature and min temperature, all considered daily. In the second example, we use the daily mean temperature measured at the weather station “Chiavari Caperana” in the Liguria Italian Region. We compare the results with our method, the average seasonal variation, Auto Regressive Integrated Moving Average (ARIMA) and the usual fuzzy transforms concluding that the best results are obtained under our approach in both examples. In addition, the comparison results show that, for seasonal time series that have no consistent irregular variations, the performance obtained with our method is comparable with the ones obtained using Support Vector Machine- and Artificial Neural Networks-based models. Full article
(This article belongs to the Special Issue Symmetry in Fuzzy Sets and Systems)
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4301 KiB  
Article
The Development of Improved Incremental Models Using Local Granular Networks with Error Compensation
by Chan-Uk Yeom and Keun-Chang Kwak
Symmetry 2017, 9(11), 266; https://doi.org/10.3390/sym9110266 - 05 Nov 2017
Cited by 3 | Viewed by 3168
Abstract
In this paper, we use the fundamental idea of the incremental model (IM) and develop the design framework. The design method of IM is composed of two steps. In the first step, we perform a linear regression (LR) as the global model. In [...] Read more.
In this paper, we use the fundamental idea of the incremental model (IM) and develop the design framework. The design method of IM is composed of two steps. In the first step, we perform a linear regression (LR) as the global model. In the second step, the errors obtained by the global model are predicted by fuzzy if-then rules generated through a local linguistic model. Although the effectiveness of IM has been demonstrated in various prediction examples, we propose an improved incremental model (IIM) to deal with complex nonlinear characteristics. For this purpose, we employ adaptive neuro-fuzzy networks (ANFN) or radial basis function networks (RBFN) to create local granular networks in the design of IIM. Furthermore, we use quadratic regression (QR) as a global model, because linear relationship of LR may not hold in many settings. Numerical studies concern four datasets (automobile data, energy efficiency data, Boston housing data and computer hardware data). The experimental results demonstrate that IIM outperformed the previous models. Full article
(This article belongs to the Special Issue Symmetry in Fuzzy Sets and Systems)
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281 KiB  
Article
Asymmetric Equivalences in Fuzzy Logic
by Bo Hu, Lvqing Bi, Sizhao Li and Songsong Dai
Symmetry 2017, 9(10), 224; https://doi.org/10.3390/sym9100224 - 13 Oct 2017
Cited by 3 | Viewed by 3492
Abstract
We introduce a new class of operations called asymmetric equivalences. Several properties of asymmetric equivalence operations have been investigated. Based on the asymmetric equivalence, quasi-metric spaces are constructed on [0, 1]. Finally, we discuss symmetrization of asymmetric equivalences. Full article
(This article belongs to the Special Issue Symmetry in Fuzzy Sets and Systems)
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248 KiB  
Article
On Characterizations of Directional Derivatives and Subdifferentials of Fuzzy Functions
by Wei Zhang, Yumei Xing and Dong Qiu
Symmetry 2017, 9(9), 177; https://doi.org/10.3390/sym9090177 - 01 Sep 2017
Cited by 1 | Viewed by 2958
Abstract
In this paper, based on a partial order, we study the characterizations of directional derivatives and the subdifferential of fuzzy function. At the same time, we also discuss the relation between the directional derivative and the subdifferential. Full article
(This article belongs to the Special Issue Symmetry in Fuzzy Sets and Systems)
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