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Mathematics
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Mathematical Methods on Intelligent Decision Support Systems
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Mathematical Methods on Intelligent Decision Support Systems

A special issue of Mathematics (ISSN 2227-7390).

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 13551

Special Issue Editor

Prof. Dr. Marcin Hernes

E-Mail Website1 Website2
Guest Editor
Center for Intelligent Management Systems, Wroclaw University of Economics and Business, 118/120 Komandorska Str., 53-345 Wroclaw, Poland
Interests: computational intelligence; artificial intelligence; cognitive technologies; knowledge management; consensus methods; multiagent systems

Special Issue Information

Dear Colleagues,

Artificial intelligence is contemporarily more often used in decision support systems. This is a response to business organizations’ needs related to analysis of a big amount of data to make satisfactory decisions. The main topics in intelligent decision support systems are related to machine learning, including deep learning, cognitive technologies, knowledge graphs, knowledge integration, internet of things, agent-based systems, blockchain-based security augmented reality, natural language processing, virtual reality, and genetic and evolutionary algorithms.

This Special Issue collects papers with the aim to develop novel mathematical methods for intelligent decision support systems and/or to apply artificial intelligence-based approaches to improve the current state-of-the-art in decision support area. Of special interest are papers that deal with the challenge of developing the deep neural networks for improving business processes.

Prof. Dr. Marcin Hernes
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • Artificial intelligence
  • Decision support systems
  • Computational intelligence
  • Deep learning

Published Papers (5 papers)

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Research

16 pages, 1576 KiB  
Article
Method of Distinguishing Styles by Fractal and Statistical Indicators of the Text as a Sequence of the Number of Letters in Its Words
by Roman Kaminskiy, Nataliya Shakhovska, Jana Kajanová and Yurii Kryvenchuk
Mathematics 2021, 9(19), 2410; https://doi.org/10.3390/math9192410 - 28 Sep 2021
Cited by 2 | Viewed by 1193
Abstract
The method of the analysis of different texts styles is developed in the paper. Integer numerical sequences are used as models. The elements of the sequence are the number of letters in the words of the text. The algorithm for calculating the exact [...] Read more.
The method of the analysis of different texts styles is developed in the paper. Integer numerical sequences are used as models. The elements of the sequence are the number of letters in the words of the text. The algorithm for calculating the exact value of the fractal dimension is developed. It provides the determination of the exact value of the Hurst index. The value of the power dependence constant is calculated. The obtained indicators in the aspect of fractality completely describe the objects of research. Full article
(This article belongs to the Special Issue Mathematical Methods on Intelligent Decision Support Systems)
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14 pages, 3174 KiB  
Article
Modeling Recoveries of US Leading Banks Based on Publicly Disclosed Data
by Pawel Siarka
Mathematics 2021, 9(2), 188; https://doi.org/10.3390/math9020188 - 19 Jan 2021
Cited by 1 | Viewed by 1721
Abstract
The credit risk management process is a critical element that allows financial institutions to withstand economic downturns. Unlike the methods regarding the probability of default, which have been deeply addressed after the financial crisis in 2008, recovery rate models still need further development. [...] Read more.
The credit risk management process is a critical element that allows financial institutions to withstand economic downturns. Unlike the methods regarding the probability of default, which have been deeply addressed after the financial crisis in 2008, recovery rate models still need further development. As there are no industry standards, leading banks are modeling recovery rates using internal models developed with different assumptions. Therefore, the outcomes are often incomparable and may lead to confusion. The author presents the concept of a unified recovery rate analysis for US banks. He uses data derived from FR Y-9C reports disclosed by the Federal Reserve Bank of Chicago. Based on the historical recoveries and credit portfolio book values, the author examines the distribution function of recoveries. The research refers to a credit card portfolio and covers nine leading US banks. The author leveraged Vasicek’s one-factor model with the asset correlation parameter and implemented it for recovery rate analysis. This experiment revealed that the estimated latent correlation ranges from 0.2% to 1.5% within the examined portfolios. They are large enough to impact the recovery rate volatility and cannot be treated as negligible. It was shown that the presented method could be applied under US Comprehensive Capital Analysis and Review exercise. Full article
(This article belongs to the Special Issue Mathematical Methods on Intelligent Decision Support Systems)
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12 pages, 1823 KiB  
Article
Interval Model of the Efficiency of the Functioning of Information Web Resources for Services on Ecological Expertise
by Mykola Dyvak, Oleksandr Papa, Andrii Melnyk, Andriy Pukas, Nataliya Porplytsya and Artur Rot
Mathematics 2020, 8(12), 2116; https://doi.org/10.3390/math8122116 - 26 Nov 2020
Cited by 39 | Viewed by 1693
Abstract
Mathematical models of the efficiency dynamics of information web resources are considered in this paper. The application of interval discrete models in the form of difference equations is substantiated and the approach to estimation of the model parameters is proposed. The proposed approach [...] Read more.
Mathematical models of the efficiency dynamics of information web resources are considered in this paper. The application of interval discrete models in the form of difference equations is substantiated and the approach to estimation of the model parameters is proposed. The proposed approach is based on the artificial bee colony algorithm (ABCA). A number of experimental studies have been carried out based on data on the functioning of web resources related to environmental monitoring services. The indicator of an information web resource user’s activity has been investigated. Three cases of model building in the form of difference equations as interval discrete models (IDM) have been considered. They vary in the general kind of expression. As a result of the computational experiments, it is shown that the adequacy of a model depends on the expression of the difference equation. In the case of its incorrect choice, the proposed method of parameters’ identification may be ineffective. The obtained interval discrete model in the difference equation form, which describes the efficiency of a web resource, makes it possible to optimize business processes in an organization that uses this web resource, as well as optimally allocate organizational resources and the workload of employees of the administrative service center. Based on the conducted experiments, the efficiency of the proposed model’s application is confirmed. Full article
(This article belongs to the Special Issue Mathematical Methods on Intelligent Decision Support Systems)
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20 pages, 1079 KiB  
Article
A Genetic Algorithm for the Shelf-Space Allocation Problem with Vertical Position Effects
by Kateryna Czerniachowska and Marcin Hernes
Mathematics 2020, 8(11), 1881; https://doi.org/10.3390/math8111881 - 30 Oct 2020
Cited by 6 | Viewed by 3402
Abstract
The shelf-space on which products are displayed is one of the most important resources in the retail environment. Therefore, decisions about shelf-space allocation and optimization are critical in retail operation management. This paper addresses the problem of a retailer who sells various products [...] Read more.
The shelf-space on which products are displayed is one of the most important resources in the retail environment. Therefore, decisions about shelf-space allocation and optimization are critical in retail operation management. This paper addresses the problem of a retailer who sells various products by displaying them on the shelf at stores. We present a practical shelf-space allocation model, based on a genetic algorithm, with vertical position effects with the objective of maximizing the retailer’s profit. The validity of the model is illustrated with example problems and compared to the CPLEX solver. The results obtained from the experimental phase show the suitability of the proposed approach. Full article
(This article belongs to the Special Issue Mathematical Methods on Intelligent Decision Support Systems)
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20 pages, 3903 KiB  
Article
A Hybrid Personnel Scheduling Model for Staff Rostering Problems
by Jiun-Yan Shiau, Ming-Kung Huang and Chu-Yi Huang
Mathematics 2020, 8(10), 1702; https://doi.org/10.3390/math8101702 - 3 Oct 2020
Cited by 5 | Viewed by 4462
Abstract
The problem of staff scheduling in the airline industry is extensively investigated in operational research studies because efficient staff employment can drastically reduce the operational costs of airline companies. Considering the flight schedule of an airline company, staff scheduling is the process of [...] Read more.
The problem of staff scheduling in the airline industry is extensively investigated in operational research studies because efficient staff employment can drastically reduce the operational costs of airline companies. Considering the flight schedule of an airline company, staff scheduling is the process of assigning all necessary staff members in such a way that the airline can operate all its flights and construct a roster line for each employee while minimizing the corresponding overall costs for the personnel. This research uses a rostering case study of the ground staff in the aviation industry as an example to illustrate the application of integrating monthly and daily schedules. The ground staff in the aviation industry case is a rostering problem that includes three different types of personnel scheduling results: fluctuation-centered, mobility-centered, and project-centered planning. This paper presents an integrated mixed integer programming (MIP) model for determining the manpower requirements and related personnel shift designs for the ground staff at the airline to minimize manpower costs. The aim of this study is to complete the planning of the monthly and daily schedules simultaneously. A case study based on real-life data shows that this model is useful for the manpower planning of ground services at the airline and that the integrated approach is superior to the traditional two-stage approach. Full article
(This article belongs to the Special Issue Mathematical Methods on Intelligent Decision Support Systems)
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