Advances in Mathematical Modeling and Related Topics

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.

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