Special Issue "Mathematical Modelling in Engineering & Human Behaviour 2019"

A special issue of Mathematical and Computational Applications (ISSN 2297-8747).

Deadline for manuscript submissions: closed (31 December 2020).

Special Issue Editors

Prof. Dr. Lucas Jódar
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Guest Editor
Institute for Multidisciplinary Mathematics, Universitat Politècnica de València, 46022 València, Spain
Interests: computational methods in finances; boundary value problems; random differential equations
Special Issues and Collections in MDPI journals
Prof. Dr. Juan Carlos Cortés
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Guest Editor
Dr. Luis Acedo Rodríguez
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Guest Editor
Institute for Multidisciplinary Mathematics, Universitat Politècnica de València, 46022 València, Spain
Interests: gravitation; modified theories of gravity; neural networks; mathematical epidemiology
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Please visit this site https://jornadas.imm.upv.es/jornadas/index.html for a detailed description of this Special Issue. The Special Issue will mainly consist of selected papers presented at the “Mathematical Modelling in Engineering & Human Behaviour 2019”. Papers that are found to fit the scope of the journal and be of sufficient quality after evaluation by the reviewers will be published free of charge. The main topics of this Special Issue are:

  • Financial mathematics;
  • Networks and applications;
  • Mathematical models in medicine;
  • Internal combustion engines;
  • Mathematical models in engineering and numerical simulation;
  • Social addictions and public health.

Prof. Dr. Lucas Jódar
Prof. Dr. Juan Carlos Cortés
Dr. Luis Acedo Rodríguez
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 papers will be 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. Mathematical and Computational Applications is an international peer-reviewed open access quarterly 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 1400 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.

Published Papers (4 papers)

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Research

Open AccessFeature PaperArticle
A Continuous Model of Marital Relations with Stochastic Differential Equations
Math. Comput. Appl. 2021, 26(1), 3; https://doi.org/10.3390/mca26010003 - 31 Dec 2020
Abstract
Marital relations depend on many factors which can increase the amount of satisfaction or unhappiness in the relation. A large percentage of marriages end up in divorce. While there are many studies about the causes of divorce and how to prevent it, there [...] Read more.
Marital relations depend on many factors which can increase the amount of satisfaction or unhappiness in the relation. A large percentage of marriages end up in divorce. While there are many studies about the causes of divorce and how to prevent it, there are very few mathematical models dealing with marital relations. In this paper, we present a continuous model based on the ideas presented by Gottman and coauthors. We show that the type of influence functions that describe the interaction between husband and wife is critical in determining the outcome of a marriage. We also introduce stochasticity into the model to account for the many factors that affect the marriage and that are not easily quantified, such as economic climate, work stress, and family relations. We show that these factors are able to change the equilibrium state of the couple. Full article
(This article belongs to the Special Issue Mathematical Modelling in Engineering & Human Behaviour 2019)
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Open AccessFeature PaperArticle
Improving Kernel Methods for Density Estimation in Random Differential Equations Problems
Math. Comput. Appl. 2020, 25(2), 33; https://doi.org/10.3390/mca25020033 - 18 Jun 2020
Abstract
Kernel density estimation is a non-parametric method to estimate the probability density function of a random quantity from a finite data sample. The estimator consists of a kernel function and a smoothing parameter called the bandwidth. Despite its undeniable usefulness, the convergence rate [...] Read more.
Kernel density estimation is a non-parametric method to estimate the probability density function of a random quantity from a finite data sample. The estimator consists of a kernel function and a smoothing parameter called the bandwidth. Despite its undeniable usefulness, the convergence rate may be slow with the number of realizations and the discontinuity and peaked points of the target density may not be correctly captured. In this work, we analyze the applicability of a parametric method based on Monte Carlo simulation for the density estimation of certain random variable transformations. This approach has important applications in the setting of differential equations with input random parameters. Full article
(This article belongs to the Special Issue Mathematical Modelling in Engineering & Human Behaviour 2019)
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Open AccessArticle
Modelling the Process to Access the Spanish Public University System Based on Structural Equation Models
Math. Comput. Appl. 2020, 25(2), 31; https://doi.org/10.3390/mca25020031 - 04 Jun 2020
Abstract
Currently, one of the challenges of universities is attracting talent in students, researchers, and teachers. The transition from high school to college requires a student to take a succession of decisions that will shape their future. For this reason, knowledge of the motivations [...] Read more.
Currently, one of the challenges of universities is attracting talent in students, researchers, and teachers. The transition from high school to college requires a student to take a succession of decisions that will shape their future. For this reason, knowledge of the motivations of the students, their family, and their personal environment, to choose a particular degree and/or university to pursue their higher studies, would allow universities to efficiently adjust their recruitment strategies. In this article, a study was developed based on a structural equation model of the access to the Spanish Public University System (SUPE), which can help with supply and demand problems, recruitment actions and policies, and other strategic decisions. This was done through an extensive survey of first-year students of Spanish universities. The results allowed us to obtain the parameters of the model, which showed that the fit between the model and the data obtained were excellent at a global level and acceptable as well in all knowledge areas. The objective of the structural model was to provide a general view of the behavior of the students when deciding the degree and university in which they are going to study, and can help in the decision making of university leaders and to understand some behaviors of the Spanish Public University System. Full article
(This article belongs to the Special Issue Mathematical Modelling in Engineering & Human Behaviour 2019)
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Open AccessArticle
Structural Stability of a Family of Exponential Polynomial Maps
Math. Comput. Appl. 2020, 25(2), 20; https://doi.org/10.3390/mca25020020 - 07 Apr 2020
Abstract
We perturbed a family of exponential polynomial maps in order to show both analytically and numerically their unpredictable orbit behavior. Due to the analytical form of the iteration functions the family has numerically different behavior than its correspondent analytical one, which is a [...] Read more.
We perturbed a family of exponential polynomial maps in order to show both analytically and numerically their unpredictable orbit behavior. Due to the analytical form of the iteration functions the family has numerically different behavior than its correspondent analytical one, which is a topic of paramount importance in computer mathematics. We discover an unexpected oscillatory parametrical behavior of the perturbed family. Full article
(This article belongs to the Special Issue Mathematical Modelling in Engineering & Human Behaviour 2019)
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