Practical Validation in a Neutrosophic Environment of the NEBS Methodology for the Optimization of SME Financing through Machine Learning

Julia; Javier; Alfonso Romero; C. del Valle

doi:https://doi.org/10.54216/IJNS.200313

Galoitica: Journal of Mathematical Structures and Applications | 2023

On The Bäcklund Transformations for Cosgrove's Equation

In this paper we study Bäcklund transformations (BTs) for Cosgrove’s equation F-XVIII. We use the generalization of Fokas and Ablowitz method to derive BT between F-XVIII and new fourth-order ordinary differential equations of Painlevé type. Moreover we derive auto-BT and give special solutions for F-XVIII.  

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Rama Asad Nadweh mail

link https://doi.org/10.54216/GJMSA.050105

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2023

Solving shortest path problems using an ant colony algorithm with triangular neutrosophic arc weights

Indeed, one of the most well-known topics in the area of graph theory is the shortest path (SP) problem, which has practical applications in various areas of research, including transportation, communication via networks, life-saving services, fire department services, etc. The edges of the connected SP problems are typically characterized by various numbers in practical applications. In this research paper, we calculate the shortest path using an ant colony optimization (ACO) algorithm with single value triangular neutrosophic numbers as arc weights. The method is used to estimate the shortest path of a neutrosophic network. One numerical example is used to test the suggested method, and outcomes are provided.

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Said Broumi mail -

Prasanta Kumar Raut mail -

Siva Prasad Behera mail

link https://doi.org/10.54216/IJNS.200410

Volume & Issue

Vol. Volume 20 / Iss. Issue 4

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American Journal of Business and Operations Research | 2021

A Case Study on the Implementation of Business Intelligence in a Retail Company

This paper presents a case study on the implementation of business intelligence (BI) in a retail company with the main aim to analyze the benefits of BI implementation and the confronts encountered during the process. The case study involves a large retail company that operates in multiple countries and offers a wide range of products. The implementation of BI was driven by the need to improve decision-making processes, increase operational efficiency, and enhance customer satisfaction. We also cover the different phases of BI implementation, including planning, data integration, data modeling, and dashboard development. The results of the study indicate that the implementation of BI has led to significant improvements in the company's performance, such as increased revenue, improved inventory management, and better customer segmentation. We investigate how artificial intelligence can provide great support for improving and automating the implementation of BI in retail companies. However, we also highlight some challenges encountered during the implementation process, such as data quality issues and resistance to change. The paper concludes by emphasizing the importance of careful planning, stakeholder engagement, and ongoing evaluation in ensuring the success of BI implementation in retail companies.

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Alshaimaa A. Tantawy mail -

Mahmoud M. Ismail mail

link https://doi.org/10.54216/AJBOR.030204

Volume & Issue

Vol. Volume 3 / Iss. Issue 2

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American Journal of Business and Operations Research | 2021

Optimizing Business Intelligence and Operations Research for Sustainable Growth: A Comparative Study of Manufacturing and Service Industries

This paper presents a comparative study of two optimization techniques, business intelligence (BI) and operations research (OR), for achieving sustainable growth in manufacturing and service industries. The study explores the strengths and weaknesses of both techniques and examines their suitability for addressing sustainability challenges in these industries. The paper also discusses various factors that influence the choice of optimization technique and presents a framework for selecting the most appropriate technique based on the problem domain, data availability, and organizational requirements. The study concludes that both BI and OR have significant potential for improving sustainability in manufacturing and service industries, and their effectiveness depends on the problem domain and organizational context. The paper provides valuable insights for researchers and practitioners interested in leveraging optimization techniques for sustainable growth.

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Mahmoud M. Ibrahim mail -

Mahmoud M. Ismail mail -

Shereen Zaki mail

link https://doi.org/10.54216/AJBOR.050104

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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American Journal of Business and Operations Research | 2021

Leveraging Business Intelligence and Operations Research for Enhanced Decision-Making in Healthcare

This paper explores the potential of leveraging business intelligence (BI) and operations research (OR) techniques to enhance decision-making in healthcare organizations. We propose a novel BI framework that includes three main components: data collection and management, data analysis and reporting, and decision-making support. Our framework leverages existing BI tools and techniques, such as data mining and visualization, to provide healthcare organizations with a comprehensive and integrated view of their operations. The framework also integrates clinical data with financial and operational data to provide a more holistic view of the organization. Healthcare organizations face numerous challenges, including rising costs, changing regulations, and the need to improve patient outcomes. By leveraging the proposed framework, healthcare organizations can make data-driven decisions that optimize resource allocation, streamline processes, and improve patient care. The paper provides use cases of how BI and OR have been successfully applied in healthcare organizations and discusses the potential for future research and applications in this field. Ultimately, our framework highlights the importance of using data-driven approaches to improve decision-making in healthcare organizations and suggests that the integration of BI and OR techniques has significant potential to achieve this goal.

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Mahmoud M. Ismail mail -

Heba R. Abdelhady mail

link https://doi.org/10.54216/AJBOR.030104

Volume & Issue

Vol. Volume 3 / Iss. Issue 1

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Journal of Artificial Intelligence and Metaheuristics | 2022

Weather Forecasting over Iraq Using Machine Learning

The weather generally comprises various factors, such as wind speed, precipitation, and rainfall. Environmental weather forecasting is a demanding task for researchers, and in recent years it has attracted much study attention. Our assessment considers a wide range of weather conditions across Iraq utilizing information gathered from NASA's estimate of the world's energy resources for the years 1981 to 2021. Therefore, the correct forecast of meteorological parameters is a difficult challenge due to their changing environmental conditions. Random forest, decision tree, and GBR algorithms are used for weather forecasting.  A comparison among used methods is performed and the RF is achieved the best results with accuracy, MAE, MSE, R2 of 92%, 0.5, 2.45, and 0.92, respectively.

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Israa Jasim Mohammed mail -

Bashar Talib Al-Nuaimi mail -

Ther Intisar Baker mail

link https://doi.org/10.54216/JAIM.020204

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Impact of Mobile Applications on Customer Service for the Tourism Sector: A Systematic Review and Neutrosophic Dematel

This study aims to systematically review mobile applications and their impact on customer service in the tourism sector from 2017 to 2021. For this, the use of the DEMATEL method in its neutrosophic variant is proposed. The search strategy identified 257,399 articles from digital libraries such as Scopus, IEEE Xplore, ACM Digital Library, Springer Link, Google Scholar, Microsoft Academic, EBSCOhost, ProQuest, ScienceDirect, and ARDI. Likewise, only 70 articles based on exclusion criteria were considered using the PRISMA Flowchart. The results of the systematic review have focused on recent studies of mobile applications and their impact on customer service in tourism and also provide a mapping of the extracted studies, metrics, trends, and validation methods to compare relevance to their settings and situations. The applicability and importance of multiple decision-making methods for solving complex problems were demonstrated. In addition, the effectiveness of using neutrosophy to reach valid conclusions when faced with real-life problems was manifested.

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Julio Oncebay-López mail -

Javier Gamboa-Cruzado mail -

Augusto Hidalgo Sánchez mail -

Violeta Benites Tirado mail

link https://doi.org/10.54216/IJNS.200411

Volume & Issue

Vol. Volume 20 / Iss. Issue 4

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International Journal of Neutrosophic Science | 2023

Analysis of Neutrosophic Elements in the Determination of Bankruptcies in SMEs Using Machine Learning

Nowadays, Machine Learning techniques stand out, especially in the business sector, in predicting bankruptcies in small and medium-sized enterprises (SMEs). This reduces the probability of making bad investments when creating SMEs. Therefore, a systematic review of Machine Learning for predicting bankruptcies in SMEs was conducted to identify ideal articles. The search was conducted on Taylor & Francis Online, IEEE Xplore, ARDI, ScienceDirect, ACM Digital Library, Google Scholar, and ProQuest. As a result, information was collected from 84 definitive studies on determining bankruptcies in SMEs using Machine Learning. Therefore, this study aims to determine the state-of-the-art regarding determining bankruptcies in SMEs using Machine Learning. To obtain the results, the Saaty Neutrosophic AHP method was used to identify the most applied business sector and predict possible bankruptcy due to its broad nature of indeterminacy in that subset. The systematic review results have allowed for determining essential details regarding the state-of-the-art of determining bankruptcies in SMEs using Machine Learning.

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J. Ramón R. de Vega mail -

A. G. Ruiz Conejo mail -

Carlos C. Carranza mail -

Vladimir R. Cairo mail

link https://doi.org/10.54216/IJNS.200412

Volume & Issue

Vol. Volume 20 / Iss. Issue 4

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International Journal of Neutrosophic Science | 2023

Systematic Review Using Neutrosophic Torgerson and Neutrosophic Vader to Determine the Impact of Mobile Applications in the Labor Integration of Disabled People

People with a disability are the most likely to end up unemployed. Knowing and finding new ways to integrate them into society is urgent in an increasingly dynamic and versatile world. The systematic Review of the literature (SRL) was developed covering the issue of labor integration of people with disabilities.. The main objective of the research was to determine the state of the art of research on Mobile Applications and their impact on the Labor Integration of People with Disabilities. The use of relationship coefficients between two neutrosophic numbers, through the Torgerson method, Allowed the evaluation of the applications by the experts. The results obtained highlight the importance of mobile technology in the process of ensuring that people with disabilities find the desired job, in addition, accessibility must be met for the correct development of the application for the various existing disabilities. By utilizing Neutro-VADER and Neutrosophy, the precision and efficiency of sentiment analysis are enhanced, especially when handling uncertain or unclear text and consulting with experts. By implementing a more intricate and refined sentiment analysis method, these tools can generate more practical and valuable perspectives regarding the sentiment of written or spoken language.

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Javier Gamboa Cruzado mail -

Julio Canales Parraga mail -

Santiago M. Benites mail -

María León Morales mail -

Liset S. Rodríguez-Baca mail

link https://doi.org/10.54216/IJNS.200312

Volume & Issue

Vol. Volume 20 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2023

Practical Validation in a Neutrosophic Environment of the NEBS Methodology for the Optimization of SME Financing through Machine Learning

Micro and small enterprises (MSEs) have generated great opportunities for the growth of countries in the Latin American region. Unfortunately, as a result of the global crisis caused by the Sar-Cov-2, MSEs were severely affected. The main objective of this investigation is to validate in a practical way in a neutrosophic environment the use of a predictive Machine Learning technique that demonstrates the probability of the return on investment that a candidate investor will obtain with respect to a given business plan. With them it is expected that the investor can make the decision to finance a MSE, with the positive decision will close gaps in the growth of micro and small enterprises in Peru. The research is descriptive and predictive, with a research design of post-test only and control group. Neutrosophic TOPSIS was used as a technique. NEBS turns out to be efficient for the applicability of Machine Learning by obtaining statistical evidence to accept the hypotheses proposed for the finance sector in micro and small en-terprises in Peru. The results showed that the use of Machine Learning is validated, and its implementation increases the amount of financing obtained, decreases the evaluation time of requirements, reduces the number of complaints, and increases the number of formal sources used. Machine Learning research should be continued due to the complexity of this technology, which is con-stantly evolving.…

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Julia Juro-Barrios mail -

Javier Gamboa-Cruzado mail -

Alfonso Romero Baylon mail -

C. del Valle Jurado mail

link https://doi.org/10.54216/IJNS.200313

Volume & Issue

Vol. Volume 20 / Iss. Issue 3

Details open_in_new