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Axioms
Special Issues
Computational and Mathematical Methods in Science and Engineering II
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Computational and Mathematical Methods in Science and Engineering II

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 4076

Special Issue Editors

Prof. Dr. Juan Frausto Solis

E-Mail Website
Guest Editor
Graduate Program Division, Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Cd. Madero 89440, Mexico
Interests: mathematical models; optimization; artificial intelligence; machine learning; folding problems; forecasting
Special Issues, Collections and Topics in MDPI journals
Dr. Juan Paulo Sánchez

E-Mail Website
Guest Editor
Dirección de Informática, Electrónica y Telecomunicaciones, Universidad Politécnica del Estado de Morelos, Jiutepec 62574, Mexico
Interests: machine learning; deep learning; optimization algorithms; computer vision
Special Issues, Collections and Topics in MDPI journals
Dr. Guadalupe Castilla Valdez

E-Mail Website
Guest Editor
Postgraduate Studies and Research Division, National Technological Institute of Mexico/Technological Institute of Ciudad Madero, Cd. Madero 89440, Mexico
Interests: combinatorial optimization; machine learning; metaheuristics; genetic algorithms; multiobjective optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a continuation of our previous Special Issue, entitled "Computational and Mathematical Methods in Science and Engineering". This Special Issue is seeking papers related to computational and mathematical methods for science and engineering. We aim to publish papers that address mathematical and computational methods in engineering and information science, which include new strategies from science and engineering areas such as differential equations, optimization, operations research, stochastic and probabilistic models, and artificial intelligence. We plan to gather high-quality contributions on new mathematical and computational methods for current problems, providing new knowledge in this scientific field.

We encourage the submission of papers from a variety of fields, including applications in physics, biology, proteomics, chemistry, finance, economy, and computational medicine. Research exploring specific areas such as pandemics concerning current problems such as COVID-19, diabetes, cancer, HIV, and other medical problems is welcome. Additionally, publications enhancing existing algorithms, methods, and mathematical analyses for important issues are welcome. Topics of interest for this Special Issue include, but are not limited to, the following subjects:

  • Computer and mathematical modeling;
  • Heuristic and exact algorithms;
  • Single- and multi-objective optimization;
  • Numerical methods for partial differential equations;
  • Forecasting for energy and climate change;
  • Machine and deep learning;
  • Dynamic systems and signal processing;
  • Big data, data mining, and data science;
  • Scheduling and timetabling;
  • Proteomics, docking, and protein folding problem.

We encourage researchers within this field to contribute original research and review papers before the deadline for this Special Issue.

Prof. Dr. Juan Frausto Solis
Dr. Juan Paulo Sánchez
Dr. Guadalupe Castilla Valdez
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. Axioms 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.

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Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Published Papers (2 papers)

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Research

18 pages, 384 KiB  
Article
Critical Permeability from Resummation
by Simon Gluzman
Axioms 2024, 13(8), 547; https://doi.org/10.3390/axioms13080547 - 11 Aug 2024
Cited by 1 | Viewed by 1186
Abstract
Special calculation methods are presented for critical indices and amplitudes for the permeability of thin wavy channels dependent on the waviness. The effective permeability and wetted perimeter of the two-dimensional random percolating media are considered as well. A special mathematical framework is developed [...] Read more.
Special calculation methods are presented for critical indices and amplitudes for the permeability of thin wavy channels dependent on the waviness. The effective permeability and wetted perimeter of the two-dimensional random percolating media are considered as well. A special mathematical framework is developed to characterize the dependencies on porosities, critical points, and indices. Various approximation techniques are applied without involving popular lubrication approximation in any sense. In particular, the Borel summation technique is applied to the effective polynomial approximations with or without optimization. Minimal difference and minimal derivative optimal conditions are adapted to calculations of critical indices and amplitudes for the effective permeability of thin wavy channels. Critical indices, amplitudes, and thresholds are obtained for the effective permeability and wetted perimeter of the two-dimensional percolating random media. Closed-form expressions for all porosities, critical points, and indices are calculated from the polynomial approximations for the first time. Full article
(This article belongs to the Special Issue Computational and Mathematical Methods in Science and Engineering II)
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16 pages, 1386 KiB  
Article
A New Criterion for Improving Convergence of Fuzzy C-Means Clustering
by Joaquín Pérez-Ortega, Carlos Fernando Moreno-Calderón, Sandra Silvia Roblero-Aguilar, Nelva Nely Almanza-Ortega, Juan Frausto-Solís, Rodolfo Pazos-Rangel and José María Rodríguez-Lelis
Axioms 2024, 13(1), 35; https://doi.org/10.3390/axioms13010035 - 2 Jan 2024
Cited by 1 | Viewed by 2050
Abstract
One of the most used algorithms to solve the fuzzy clustering problem is Fuzzy C-Means; however, one of its main limitations is its high computational complexity. It is known that the efficiency of an algorithm depends, among other factors, on the strategies for [...] Read more.
One of the most used algorithms to solve the fuzzy clustering problem is Fuzzy C-Means; however, one of its main limitations is its high computational complexity. It is known that the efficiency of an algorithm depends, among other factors, on the strategies for its initialization and convergence. In this research, a new convergence strategy is proposed, which is based on the difference of the objective function values, in two consecutive iterations, expressed as a percentage of its value in the next to the last one. Additionally, a new method is proposed to optimize the selection of values of the convergence or stop threshold of the algorithm, which is based on the Pareto principle. To validate our approach, a collection of real datasets was solved, and a significant reduction in the number of iterations was observed, without affecting significantly the solution quality. Based on the proposed method and the experiments carried out, we found it is convenient to use threshold values equal to 0.73 and 0.35 if a decrease in the number of iterations of approximately 75.2% and 64.56%, respectively, is wanted, at the expense of a reduction in solution quality of 2% and 1%, respectively. It is worth mentioning that, as the size of the datasets is increased, the proposed approach tends to obtain better results, and therefore, its use is suggested for datasets found in Big Data and Data Science. Full article
(This article belongs to the Special Issue Computational and Mathematical Methods in Science and Engineering II)
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