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International Journal of Neutrosophic Science | 2021

n-Valued Refined Neutrosophic Crisp Sets

The main purpose of this manuscript is to expand the notion of neutrosophic crisp set (NCS) by presenting the notion of n-valued refined neutrosophic crisp set with some illustration examples. We also establish some of its set-theoretical operations.

groups
Ahmed B. AL-Nafee mail -
Said Broumi mail -
Luay A. Al-Swidi mail
link https://doi.org/10.54216/IJNS.170201

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new
International Journal of Neutrosophic Science |

A New Approach Of Supra-Neutrosophic Topological space

In this new paper, we introduced new and important concepts in neutrosophic topology for the first time. Where we introduced the interesting concept "a new approach of neutrosophic supra-topological space (ŠNǺ-NTS)", that we presented this neutrosophic supra-topological space without using neutrosophic sets, and we also studied the separation axioms in this new neutrosophic supra-space and studied the relationship between the new separation axioms in (ŠNǺ-NTS) and the separation axioms of the previously known supra-topological space. We also defined the neutrosophic supra-topological sup-space from this new space. We prove that ŠNǺ-NTS is not a classical supra-topological space. Also, ŠNǺ-NTS is neither neutrosophic supra-topological space nor neutrosophic crisp topological space. Many examples and theories are presented.

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RiadKAlHamido mail
link

Volume & Issue

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American Journal of Business and Operations Research | 2023

A Decision Support System for Credit Risk Assessment using Business Intelligence and Machine Learning Techniques

Credit risk assessment is a critical task for financial institutions to determine the creditworthiness of their potential customers. Business intelligence (BI) and machine learning (ML) techniques have gained popularity in recent years as effective tools for credit risk assessment. In this paper, we propose a decision support system (DSS) for credit risk assessment that integrates BI and ML techniques. The proposed DSS employs BI tools to extract and transform data from various sources, and ML techniques to analyze the data and generate predictive models for credit risk assessment. We evaluate the proposed DSS using a real-world dataset of a financial institution. The results show that the proposed DSS achieves a high level of accuracy in credit risk assessment. The results showed that the system was able to accurately predict credit risk, with an accuracy of 88%. The system also outperformed traditional credit scoring models, which highlights the potential of our system for credit risk assessment. The system provides decision-makers with actionable insights to make informed decisions, thereby reducing the risk of default and increasing the profitability of the financial institution.

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Khyati Chaudhary mail -
Gopal Chaudhary mail
link https://doi.org/10.54216/AJBOR.100204

Volume & Issue

Vol. Volume 10 / Iss. Issue 2

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American Journal of Business and Operations Research | 2023

A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce

This paper presents a comparative analysis of traditional forecasting methods and machine learning (ML) techniques for sales prediction in e-commerce.  We first review the literature on both traditional and ML methods for sales prediction in e-commerce, highlighting their strengths and weaknesses. The study uses a dataset of daily sales from an e-commerce retailer to conduct a comprehensive empirical study thar compares the performance of literature methods from both categories. The analysis considers different forecasting horizons and evaluates the accuracy of the predictions using various performance metrics, such as mean absolute error and mean squared error. The study finds that ML techniques generally outperform traditional methods, especially for longer forecasting horizons. However, some traditional methods, such as the Holt-Winters method, can also perform well under certain conditions. Our study provides insights into the relative strengths and weaknesses of traditional and ML methods for sales prediction in e-commerce and can guide practitioners in selecting appropriate methods for their specific requirements.

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Irina V. Pustokhina mail -
Denis A. Pustokhin mail
link https://doi.org/10.54216/AJBOR.100205

Volume & Issue

Vol. Volume 10 / Iss. Issue 2

Details open_in_new
American Journal of Business and Operations Research | 2021

Data-Driven Approach for Enhancing Customer Satisfaction: A Case Study in Service Operations Management

 In today's highly competitive business environment, companies are increasingly focusing on enhancing customer satisfaction to improve customer loyalty and drive business growth. In this context, the use of data-driven approaches can provide valuable insights for companies to improve their service quality and customer experience. This paper presents a case study in service operations management, where a data-driven approach is used to enhance customer satisfaction. We employ a dataset of customer feedback from a service company and proposes a deep learning (DL) algorithm learn to identify the factors that affect customer satisfaction. The results show that the proposed data-driven approach is effective in identifying the key drivers of customer satisfaction and in providing actionable insights for service improvement. We highlight the potential of our DL approach for enhancing customer satisfaction and provides insights for service companies to improve their customer experience based on the analysis of customer feedback.

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Alshaimaa A. Tantawy mail -
Heba R. Abdelhady mail -
Shereen Zaki mail -
Mahmoud M. Ismail mail
link https://doi.org/10.54216/AJBOR.020105

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new
Neutrosophic and Information Fusion | 2023

A Multi-Criteria Decision-Making Approach for Piston Material Selection under Single-Valued Trapezoidal Neutrosophic Sets

It is one of the most difficult and time-consuming processes to develop and pick an acceptable material for the piston material that has a variety of attributes. Component failure is often caused by inappropriate material at some stage throughout the functioning process. In light of this, the piston material selection is performed in this article. The goal of this work is to found a technique for selecting the material of the piston for a new design engine by using the multi-criteria decision-making (MCDM) approach to find a solution to the issue of choosing the material for the piston. The purpose of the TOPSIS method is to pick the appropriate material for a piston based on the application it will be used in. The TOPSIS technique is stretched under neutrosophic sets to solve the vague and uncertain information in this process. The single-valued trapezoidal neutrosophic sets (SVTNSs) are used in this paper. The SVTNSs is a mixed with the trapezoidal neutrosophic sets (TNSs) and the single-valued neutrosophic sets (SVNSs). There are nine criteria and three alternatives used in this paper. The illustrative example is carried out The sensitivity analysis and comparative study are carried out to display the robustness and efficiency of the suggested model.

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Ahmed M. Ali mail
link https://doi.org/10.54216/NIF.020102

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new
Neutrosophic and Information Fusion | 2023

An Integrated Multi-Criteria Decision-Making Approach for Identification and Ranking Solar Drying Barriers under Single-Valued Triangular Neutrosophic Sets (SVTNSs)

Solar dryers utilized in agriculture for the drying of food and crops are also utilized for drying operations in industrial settings. They have the potential to be shown as a very helpful tool in terms of the management of energy saving. It not only helps conserve energy, but it also helps save a lot of time, consumes less space, makes the procedure more effective, enhances the standard of the product, and safeguards the surroundings. Due to the many associated potential barriers, the acceptance of solar dryers has not yet reached a benchmark, although this was an expectation. In this body of work, a methodical framework that makes use of the MCDM tools has been proposed to identify and rank several obstacles in descending order of importance.The AHP can identify both quantitative and qualitative aspects by using comparison matrices to assign weights to them and rank them in order of importance. The AHP technique is used to calculate the weights and relationship of the solar drying barrier. To account for the lack of clarity and coherence in the data that is available in the actual world, we tested the suggested model in a neutrosophic set. We used the single-valued triangular neutrosophic sets (SVTNSs). SVTNSs are a type of neutrosophic set, integrated into triangular neutrosophic sets and SVNSs. The application of applying the SVNSs-AHP is performed.

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Shimaa Said mail -
Mahmoud M. Ibrahim mail -
Mahmoud M. Ismail mail
link https://doi.org/10.54216/NIF.020103

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new
Neutrosophic and Information Fusion | 2023

Financial Risks Appraisal based on Dynamic Appraisal Framework

Recently, New Energy Vehicle (NEV) consider eco-friendly and become the strategic option for balancing economic, social, and ecological goals. Therefore, this study contributed to construct a dynamic appraisal framework (DAF). Deploying Combined Compromise Solution (CoCoSo) methods and single-valued neutrosophic sets (SNNSs) in DAF to appraise financial risk for seven enterprises based on determined nine criteria. The CoCoSo method is used within the context of the SVN to decide which enterpise is the otimal. In addition, an example case study of financial risk evaluation is explored to highlight the entire execution process of the suggested framework.

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Mona Mohamed mail
link https://doi.org/10.54216/NIF.020104

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new
Neutrosophic and Information Fusion | 2023

Spherical Fuzzy Multi-Criteria Decision-Making Approach for Risk Assessment of Natech

It is possible for a natural catastrophe to cause harm to numerous industrial facilities in the same region simultaneously. The natural catastrophe's Natech events may then affect the industrial facilities that are located nearby, so creating a coupling risk. The evaluation of the danger of Natech events coupling is conducted using the technique of multi-criteria decision-making (MCDM) methodology in this investigation. Additionally, the concept of spherical fuzzy is presented as a means of resolving the issue of ambiguity associated with the Natech coupling risk. The Natech Coupling Hazard Index is designed to include both tangible and operational resources in its calculations. The idea of an equal population is being floated as a means of contrasting the dangers presented by physical facilities with those posed by functional amenities. The spherical fuzzy set is an effective method for coping with ambiguity since it presents a broader decision-making region and identifies reluctance. under this paper, a fuzzy MDCM technique using spherical fuzzy AHP is proposed as a solution to the challenge of managing the selection of process mining methods under settings that are unclear and vague. The AHP method is used to compute the weights of criteria and shows the rank and order of alternatives. The application is performed in steps of the spherical fuzzy AHP method.

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Hadeer Mahmoud mail -
Ahmed Abdelhafeez mail
link https://doi.org/10.54216/NIF.020105

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new