Symmetry in Data Sciences and Machine Learning for Multidisciplinary Research

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 29

Special Issue Editors


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Guest Editor
Department of Mechatronics, Polytechnic University of Pachuca (UPP), Zempoala, Hidalgo, Mexico
Interests: automatic control; fuzzy logic; microcontroller programming; fault diagnosis; bio-inspired algorithms

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Guest Editor
Ocean College, Zhejiang University, Zhoushan 316021, China
Interests: fractal time series; long-range dependent processes; self-similar processes; fractional derivative; fractional processes; fractional oscillation equation; fractional Brownian motion; fractional Gaussian noise and its applications; ships and ocean engineering; network traffic; computer science; mathematics; statistics; mechanics; systems sciences
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Guest Editor
Telematics Engineering Department, Polytechnic University of Pachuca, Zempoala, Mexico
Interests: signal and image processing; artificial intelligence; adaptive filters; stochastic models; embedded systems; educational technology

Special Issue Information

Dear Colleagues,

This Special Issue focuses on exploring symmetry and asymmetry in data sciences and machine learning for multidisciplinary research. Topics addressed include data analysis, data mining, data-driven fault diagnosis, machine learning, spiking neural networks, deep learning, fuzzy logic, fuzzy control, swarm intelligence, bio-inspired algorithms, automation, and the Internet of Things. Applications in fields such as materials science, biomedical engineering, environmental monitoring, robotics, financial forecasting, and smart infrastructure are encouraged. Additionally, the challenges and opportunities associated with data distributions, whether Gaussian, normal, or skewed, and their treatment within these applications are highlighted. Researchers are invited to submit original works that promote interdisciplinary collaboration and innovation in these areas, with a particular emphasis on practical applications in science and engineering.

Prof. Dr. Marco Antonio Márquez-Vera
Prof. Dr. Ming Li
Dr. Eric Simancas-Acevedo
Guest Editors

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
  • asymmetry
  • data analysis
  • machine learning
  • data mining
  • fault diagnosis
  • spiking neural networks
  • swarm intelligence
  • data distribution

Published Papers

This special issue is now open for submission.
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