Selected Papers from ESM 2019

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (1 March 2020) | Viewed by 26064

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Guest Editor
Department of Mathematics and Computer Science, Universitat de les Illes Balears, Palma de Mallorca, Spain
Interests: mathematical modelling; fuzzy sets; generalized distances; aggregation operators; data mining; multidisciplinary applications
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Guest Editor
Department of Mathematics and Computer Science, Universitat de les Illes Balears, 07122 Palma, Spain
Interests: information fusion; aggregation functions; decision making methods; generalized metric structures; similarity measures; fixed point theory; applications to engineering, economics and medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 33rd annual European Simulation and Modelling Conference (ESM 2019) will be held on 28–30 October 2019, at UIB, Palma de Mallorca, Spain. ESM 2019 aims to provide an overview of academic research in the field of mathematical modeling and computer simulation. A number of major tracks of simulation research are presented next to specific workshops, which capture the art and science of present-day simulation research. For more information, see: https://www.eurosis.org/conf/esm/2019/.

The authors of a number of selected full papers of high quality will be invited after the conference to submit revised and extended versions of their originally-accepted conference papers to this Special Issue of Information, published by MDPI, in open access. The selection of these best papers will be based on their ratings in the conference review process, quality of presentation during the conference, and expected impact on the research community. Each submission to this Special Issue should contain at least 50% of new material, e.g., in the form of technical extensions, more in-depth evaluations, or additional use cases and a change of title, abstract, and keywords. These extended submissions will undergo a peer-review process according to the journal’s rules of action. At least two technical committees will act as reviewers for each extended article submitted to this Special Issue; if needed, additional external reviewers will be invited to guarantee a high-quality reviewing process. All selected papers will be free of charge.

Dr. Pilar Fuster Parra
Dr. Óscar Valero Sierra
Guest Editors

Manuscript Submission Information

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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. Information 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 1600 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

  • Modeling methodology
  • Modeling simulation tools
  • Object-orientation and re-use
  • Random Monte Carlo simulations and applications
  • Discrete and continuous simulation modelling techniques and tools
  • Queueing models
  • Monte Carlo simulation
  • Simulation and AI
  • AI and expert systems
  • AI and neural networks
  • AI and fuzzy systems
  • Agent-based simulation
  • Simulation and optimization
  • IoT and smart industry (Internet of Things and Industry 4.0)
  • High performance/parallel and large-scale computing
  • Simulation in education and graphics/data visualization
  • Simulation in environmental ecology, marine biology, and biology
  • Simulation in biological systems and medicine
  • Analytical and numerical modeling techniques
  • Web-based simulation
  • Cloud-based simulation
  • Physics modeling and cosmological simulation
  • Decision-making methods

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Published Papers (5 papers)

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Research

21 pages, 1032 KiB  
Article
Algorithmic Improvements of the KSU-STEM Method Verified on a Fund Portfolio Selection
by Adam Borovička
Information 2020, 11(5), 262; https://doi.org/10.3390/info11050262 - 12 May 2020
Cited by 2 | Viewed by 2627
Abstract
The topic of this article is inspired by the problem faced by many people around the world: investment portfolio selection. Apart from the standardly used methods and approaches, non-traditional multiple objective programming methods can also be significant, providing even more efficient support for [...] Read more.
The topic of this article is inspired by the problem faced by many people around the world: investment portfolio selection. Apart from the standardly used methods and approaches, non-traditional multiple objective programming methods can also be significant, providing even more efficient support for making a satisfactory investment decision. A more suitable method for this purpose seems to be a concept working with an interactive procedure through the portfolio that may gradually be adapted to the investor’s preferences. Such a method is clearly the Step Method (STEM) or the more suitable improved version KSU-STEM. This method is still burdened by partial algorithmic weaknesses or methodical aspects to think about, but not as much as the other methods. The potentially stronger application power of the KSU-STEM concept motivates its revision. Firstly, an unnecessarily negative principle to determine the basal value of the objectives is revised. Further, the fuzzy goals are specified, which leads to a reformulation of the revealed defuzzified multi-objective model. Finally, the imperfect re-setting of the weights (importance) of unsatisfactory objectives is revealed. Thus, the alternative approaches are proposed. The interventions to the algorithm are empirically verified through a real-life selection of a portfolio of the open unit trusts offered by CONSEQ Investment Management traded on the Czech capital market. This application confirms a significant supporting power of the revised multiple objective programming approach KSU-STEM in a portfolio-making process. Full article
(This article belongs to the Special Issue Selected Papers from ESM 2019)
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30 pages, 6397 KiB  
Article
Fvsoomm a Fuzzy Vectorial Space Model and Method of Personality, Cognitive Dissonance and Emotion in Decision Making
by Joël Colloc
Information 2020, 11(4), 229; https://doi.org/10.3390/info11040229 - 21 Apr 2020
Cited by 6 | Viewed by 4212
Abstract
The purpose of this extension of the ESM’2019 conference paper is to propose some means to implement an artificial thinking model that simulates human psychological behavior. The first necessary model is the time fuzzy vector space model (TFVS). Traditional fuzzy logic uses fuzzification/defuzzification, [...] Read more.
The purpose of this extension of the ESM’2019 conference paper is to propose some means to implement an artificial thinking model that simulates human psychological behavior. The first necessary model is the time fuzzy vector space model (TFVS). Traditional fuzzy logic uses fuzzification/defuzzification, fuzzy rules and implication to assess and combine several significant attributes to make deductions. The originality of TFVS is not to be another fuzzy logic model but rather a fuzzy object-oriented model which implements a dynamic object structural, behavior analogy and which encapsulates time fuzzy vectors in the object components and their attributes. The second model is a fuzzy vector space object oriented model and method (FVSOOMM) that describes how-to realize step by step the appropriate TFVS from the ontology class diagram designed with the Unified Modeling Language (UML). The third contribution concerns the cognitive model (Emotion, Personality, Interactions, Knowledge (Connaissance) and Experience) EPICE the layers of which are necessary to design the features of the artificial thinking model (ATM). The findings are that the TFVS model provides the appropriate time modelling tools to design and implement the layers of the EPICE model and thus the cognitive pyramids of the ATM. In practice, the emotion of cognitive dissonance during buying decisions is proposed and a game addiction application depicts the gamer decision process implementation with TFVS and finite state automata. Future works propose a platform to automate the implementation of TFVS according to the steps of the FVSOOMM method. An application is a case-based reasoning temporal approach based on TFVS and on dynamic distances computing between time resultant vectors in order to assess and compare similar objects’ evolution. The originality of this work is to provide models, tools and a method to design and implement some features of an artificial thinking model. Full article
(This article belongs to the Special Issue Selected Papers from ESM 2019)
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11 pages, 2886 KiB  
Article
The Effect of Augmented Reality on Students’ Learning Performance in Stem Education
by Plamen D. Petrov and Tatiana V. Atanasova
Information 2020, 11(4), 209; https://doi.org/10.3390/info11040209 - 15 Apr 2020
Cited by 61 | Viewed by 13112
Abstract
The effect of one of the most popular 3D visualization and modelling technologies with haptic and touch feedback possibilities—augmented reality (AR)—is analysed herein. That includes a specific solution, incorporating augmented reality. A case study for delivering STEM (science, technology, engineering, and mathematics) content [...] Read more.
The effect of one of the most popular 3D visualization and modelling technologies with haptic and touch feedback possibilities—augmented reality (AR)—is analysed herein. That includes a specific solution, incorporating augmented reality. A case study for delivering STEM (science, technology, engineering, and mathematics) content using this tool at one secondary school in Sofia is presented. The experience gained in one school year of using facilities for a STEM enrichment program has been examined. Full article
(This article belongs to the Special Issue Selected Papers from ESM 2019)
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13 pages, 2484 KiB  
Article
Stochastic Model of Spatial Fields of the Average Daily Wind Chill Index
by Nina Kargapolova
Information 2020, 11(4), 177; https://doi.org/10.3390/info11040177 - 26 Mar 2020
Cited by 3 | Viewed by 2441
Abstract
The objective of this paper was to construct a numerical stochastic model of the spatial field of the average daily wind chill index on an irregular grid defined by the location of the weather stations. It is shown in the paper that the [...] Read more.
The objective of this paper was to construct a numerical stochastic model of the spatial field of the average daily wind chill index on an irregular grid defined by the location of the weather stations. It is shown in the paper that the field in question was heterogeneous and non-Gaussian. A stochastic model based on the real data collected at the weather stations located in West Siberia and on the method of the inverse distribution function that sufficiently well reproduce different characteristics of the real field of the average daily wind chill index is proposed in this paper. I also discussed several questions related to the simulation of the field on a regular grid. In the future, my intention is to transform the model proposed to a model of the conditional spatio-temporal field defined on a regular grid that allows one to forecast the wind chill index. Full article
(This article belongs to the Special Issue Selected Papers from ESM 2019)
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13 pages, 2036 KiB  
Article
Recursive Matrix Calculation Paradigm by the Example of Structured Matrix
by Jerzy S. Respondek
Information 2020, 11(1), 42; https://doi.org/10.3390/info11010042 - 13 Jan 2020
Cited by 2 | Viewed by 2999
Abstract
In this paper, we derive recursive algorithms for calculating the determinant and inverse of the generalized Vandermonde matrix. The main advantage of the recursive algorithms is the fact that the computational complexity of the presented algorithm is better than calculating the determinant and [...] Read more.
In this paper, we derive recursive algorithms for calculating the determinant and inverse of the generalized Vandermonde matrix. The main advantage of the recursive algorithms is the fact that the computational complexity of the presented algorithm is better than calculating the determinant and the inverse by means of classical methods, developed for the general matrices. The results of this article do not require any symbolic calculations and, therefore, can be performed by a numerical algorithm implemented in a specialized (like Matlab or Mathematica) or general-purpose programming language (C, C++, Java, Pascal, Fortran, etc.). Full article
(This article belongs to the Special Issue Selected Papers from ESM 2019)
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