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Symmetry
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Symmetry in Nonlinear Studies II
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Symmetry in Nonlinear Studies II

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 1559

Special Issue Editor

Prof. Dr. Manuel De La Sen

E-Mail Website
Guest Editor
Department of Electricity and Electronics, Faculty of Science and Technology, University of the Basque Country, P.O. Box 644 Bilbao, Spain
Interests: dynamic systems; sampled-data systems ( with an emphasis on non-uniform sampling); stability of dynamic systems and stability of differential and difference equations; epidemic mathematical models
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The properties of symmetry are very relevant in certain problems of theoretical physics and mathematics, as well as in many applications, for instance, related to Noether-type theorems, Lie symmetry, conservation laws, or studies of biological and medical problems modelled based on patchy environments. These problems are important for the theoretical development of “ad hoc” models of differential-difference equations or those based on graph theory. However, there are also real problems where the symmetry is either lost or not taken formally into account to derive the expected relevant properties—for instance, those related to asymmetric patchy environments in epidemic models or the formal use of frameworks of quasimetrics rather than metrics in fixed-point theory and some of its applications. This Special Issue of the journal Symmetry invites contributions illustrating the bridges between mathematical and real-life scientific or applied problems and the relevance to them of symmetry- and/or asymmetry-related physical or modeling constraints. A tentative list of topics of interest for the issue follows below, but the issue is also open to other related topics.

Prof. Dr. Manuel De La Sen
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

  • control systems
  • biological systems
  • epidemic models
  • fractional calculus
  • dynamic systems
  • stability

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Published Papers (1 paper)

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Research

16 pages, 4892 KiB  
Article
A Novel Hybrid Method Based on the Marine Predators Algorithm and Adaptive Neuro-Fuzzy Inference System for the Identification of Nonlinear Systems
by Ceren Baştemur Kaya
Symmetry 2023, 15(9), 1765; https://doi.org/10.3390/sym15091765 - 15 Sep 2023
Cited by 5 | Viewed by 1011
Abstract
In this study, a hybrid method based on the marine predators algorithm (MPA) and adaptive neuro-fuzzy inference system (ANFIS) is presented to identify nonlinear systems exhibiting symmetrical or asymmetrical behavior. In other words, the antecedent and conclusion parameters of the ANFIS are adjusted [...] Read more.
In this study, a hybrid method based on the marine predators algorithm (MPA) and adaptive neuro-fuzzy inference system (ANFIS) is presented to identify nonlinear systems exhibiting symmetrical or asymmetrical behavior. In other words, the antecedent and conclusion parameters of the ANFIS are adjusted by the MPA. The performance of the MPA is evaluated on eight nonlinear systems. The mean squared error is used as the error metric. Successful results were obtained on the eight systems. The best mean training error values belonging to the eight systems are 1.6 × 10−6, 3.2 × 10−3, 1.5 × 10−5, 9.2 × 10−6, 3.2 × 10−5, 2.3 × 10−3, 1.7 × 10−5, and 8.7 × 10−6. In the ANFIS training carried out to solve the related problems, the performance of the MPA was compared with the butterfly optimization algorithm, the flower pollination algorithm, moth–flame optimization, the multi-verse optimizer, the crystal structure algorithm, the dandelion optimizer, the RIME algorithm, and the salp swarm algorithm. The results have shown that the performance of the MPA mostly outperforms other algorithms in both training and testing processes. Full article
(This article belongs to the Special Issue Symmetry in Nonlinear Studies II)
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