Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
1.9
Journals
Axioms
Special Issues
Advances in Mathematical Modeling and Related Topics
share announcement

Advances in Mathematical Modeling and Related Topics

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

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1008

Special Issue Editor

Prof. Dr. En-Bing Lin

E-Mail Website
Guest Editor
School of Computing and Data Science, Wentworth Institute of Technology, Boston, MA 02132, USA
Interests: mathematical physics; complex geometry; applied and computational mathematics; wavelet analysis and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mathematical modeling is a powerful tool for understanding systems across engineering, biology, economics, environmental science, and more. We are excited to announce this Special Issue, entitled "Advances in Mathematical Modeling and Related Topics", showcasing the latest developments in this field. This Special Issue will provide a platform for researchers to present innovative models addressing complex real-world problems. It also offers opportunities to review themes, explore unaddressed aspects, propose new approaches, exchange perspectives, and inspire new research directions.

Topics of interest include, but are not limited to, the following: numerical methods for PDEs; dynamical systems; mathematical models of tumor growth; symmetry in nonlinear dynamics; AI and machine learning models; biomechanical systems modeling; stochastic processes in finance; optimization in industry applications; population dynamics in mathematical biology; topological data analysis; simulation in computational fluid dynamics; epidemiological models for public health; climate change mathematical predictions; quantum mechanics models; big data analysis techniques; rough set theory; bioinformatics for proteomics; formal concept analysis; fuzzy set theory and applications; granular computing in data analysis; wavelet-based image compression and denoising; rough-fuzzy hybrid models; wavelet analysis in time-series forecasting; supply chain optimization; game theory in economics; wave propagation in media; heat transfer models; quantum computing algorithms; signal processing techniques; image processing algorithms; elasticity and plasticity in materials; population genetics models; Bayesian inference applications; complex network dynamics; discrete mathematics applications; inverse problems in engineering; geophysical phenomena modeling; neural network optimization; materials science mathematical models; mathematical ecology; health care system modeling; and genomic data analysis.

We invite researchers specializing in these fields to submit their work for consideration. Contributions may be submitted on a rolling basis until the deadline and will undergo a peer-review process to ensure selection based on quality and relevance. 

Prof. Dr. En-Bing Lin
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. 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.

Keywords

  • mathematical modeling
  • numerical methods for PDEs
  • AI and machine learning models
  • wavelet analysis in time-series forecasting
  • mathematical models of tumor growth

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

27 pages, 383 KiB  
Article
Qualitative Analysis of Stochastic Caputo–Katugampola Fractional Differential Equations
by Zareen A. Khan, Muhammad Imran Liaqat, Ali Akgül and J. Alberto Conejero
Axioms 2024, 13(11), 808; https://doi.org/10.3390/axioms13110808 - 20 Nov 2024
Viewed by 304
Abstract
Stochastic pantograph fractional differential equations (SPFDEs) combine three intricate components: stochastic processes, fractional calculus, and pantograph terms. These equations are important because they allow us to model and analyze systems with complex behaviors that traditional differential equations cannot capture. In this study, we [...] Read more.
Stochastic pantograph fractional differential equations (SPFDEs) combine three intricate components: stochastic processes, fractional calculus, and pantograph terms. These equations are important because they allow us to model and analyze systems with complex behaviors that traditional differential equations cannot capture. In this study, we achieve significant results for these equations within the context of Caputo–Katugampola derivatives. First, we establish the existence and uniqueness of solutions by employing the contraction mapping principle with a suitably weighted norm and demonstrate that the solutions continuously depend on both the initial values and the fractional exponent. The second part examines the regularity concerning time. Third, we illustrate the results of the averaging principle using techniques involving inequalities and interval translations. We generalize these results in two ways: first, by establishing them in the sense of the Caputo–Katugampola derivative. Applying condition β=1, we derive the results within the framework of the Caputo derivative, while condition β→0+ yields them in the context of the Caputo–Hadamard derivative. Second, we establish them in Lp space, thereby generalizing the case for p=2. Full article
(This article belongs to the Special Issue Advances in Mathematical Modeling and Related Topics)
16 pages, 495 KiB  
Article
A Kinematic Approach to the Classical SIR Model
by Fernando Córdova-Lepe, Juan Pablo Gutiérrez-Jara and Katia Vogt-Geisse
Axioms 2024, 13(10), 718; https://doi.org/10.3390/axioms13100718 - 16 Oct 2024
Viewed by 411
Abstract
Given the risk and impact of infectious-contagious X diseases, which are expected to increase in frequency and unpredictability due to climate change and anthropogenic penetration of the wilderness, it is crucial to advance descriptions and explanations that improve the understanding and applicability of [...] Read more.
Given the risk and impact of infectious-contagious X diseases, which are expected to increase in frequency and unpredictability due to climate change and anthropogenic penetration of the wilderness, it is crucial to advance descriptions and explanations that improve the understanding and applicability of current theories. An inferential approach is to find analogies with better-studied contexts from which new questions and hypotheses can be raised through their concepts, propositions, and methods. Kinematics emerges as a promising analog field in physics by interpreting states’ changes in a contagion process as a movement. Consequently, this work explores, for a contagion process, the representations and conceptual equivalents for position, displacement, velocity, momentum, and acceleration, introducing some metrics. It also discusses some epistemological aspects and proposes future perspectives. Full article
(This article belongs to the Special Issue Advances in Mathematical Modeling and Related Topics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop