Axioms

Editorial

Jump to: Research

3 pages, 337 KiB

Open AccessEditorial

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

by Amit K. Shukla

Axioms 2022, 11(11), 615; https://doi.org/10.3390/axioms11110615 - 5 Nov 2022

Viewed by 1250

Abstract

With more than 50 years of literature, fuzzy logic has gradually progressed from an emerging field to a developed research domain, incorporating the sub-domain of mathematical fuzzy logic (MFL) [...] Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

Research

Jump to: Editorial

37 pages, 8571 KiB

Open AccessArticle

Research Agenda on Multiple-Criteria Decision-Making: New Academic Debates in Business and Management

by Fernando Castelló-Sirvent and Carlos Meneses-Eraso

Axioms 2022, 11(10), 515; https://doi.org/10.3390/axioms11100515 - 29 Sep 2022

Cited by 5 | Viewed by 2398

Abstract

Systemic disruptions are becoming more continuous, intense, and persistent. Their effects have a severe impact on the economy in volatile, uncertain, complex, and ambiguous (VUCA) environments that are increasingly transversal to productive sectors and activities. Researchers have intensified their academic production of multiple-criteria [...] Read more.

Systemic disruptions are becoming more continuous, intense, and persistent. Their effects have a severe impact on the economy in volatile, uncertain, complex, and ambiguous (VUCA) environments that are increasingly transversal to productive sectors and activities. Researchers have intensified their academic production of multiple-criteria decision-making (MCDM) in recent years. This article analyzes the research agenda through a systematic review of scientific articles in the Web of Science Core Collection according to the Journal Citation Report (JCR), both in the Social Sciences Citation Index (SSCI) and in the Science Citation Index Expanded (SCIE). According to the selected search criteria, 909 articles on MCDM published between 1979 and 2022 in Web of Science journals in the business and management categories were located. A bibliometric analysis of the main thematic clusters, the international collaboration networks, and the bibliographic coupling of articles was carried out. In addition, the analysis period is divided into two subperiods (1979–2008 and 2009–2022), establishing 2008 as the threshold, the year of the Global Financial Crisis (GFC), to assess the evolution of the research agenda at the beginning of systemic disruptions. The bibliometric analysis allows the identification of the motor, basic, specialized, and emerging themes of each subperiod. The results show the similarities and differences between the academic debate before and after the GFC. The evidence found allows academics to be guided in their high-impact research in business and management using MCDM methodologies to address contemporary challenges. An important contribution of this study is to detect gaps in the literature, highlighting unclosed gaps and emerging trends in the field of study for journal editors. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

15 pages, 4493 KiB

Open AccessArticle

Explainable Fuzzy AI Challenge 2022: Winner’s Approach to a Computationally Efficient and Explainable Solution

by Sunny Mishra, Amit K. Shukla and Pranab K. Muhuri

Axioms 2022, 11(10), 489; https://doi.org/10.3390/axioms11100489 - 20 Sep 2022

Cited by 4 | Viewed by 2791

Abstract

An explainable artificial intelligence (XAI) agent is an autonomous agent that uses a fundamental XAI model at its core to perceive its environment and suggests actions to be performed. One of the significant challenges for these XAI agents is performing their operation efficiently, [...] Read more.

An explainable artificial intelligence (XAI) agent is an autonomous agent that uses a fundamental XAI model at its core to perceive its environment and suggests actions to be performed. One of the significant challenges for these XAI agents is performing their operation efficiently, which is governed by the underlying inference and optimization system. Along similar lines, an Explainable Fuzzy AI Challenge (XFC 2022) competition was launched, whose principal objective was to develop a fully autonomous and optimized XAI algorithm that could play the Python arcade game “Asteroid Smasher”. This research first investigates inference models to implement an efficient (XAI) agent using rule-based fuzzy systems. We also discuss the proposed approach (which won the competition) to attain efficiency in the XAI algorithm. We have explored the potential of the widely used Mamdani- and TSK-based fuzzy inference systems and investigated which model might have a more optimized implementation. Even though the TSK-based model outperforms Mamdani in several applications, no empirical evidence suggests this will also be applicable in implementing an XAI agent. The experimentations are then performed to find a better-performing inference system in a fast-paced environment. The thorough analysis recommends more robust and efficient TSK-based XAI agents than Mamdani-based fuzzy inference systems. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

20 pages, 1981 KiB

Open AccessArticle

Combining Students’ Grades and Achievements on the National Assessment of Knowledge: A Fuzzy Logic Approach

by Daniel Doz, Darjo Felda and Mara Cotič

Axioms 2022, 11(8), 359; https://doi.org/10.3390/axioms11080359 - 23 Jul 2022

Cited by 4 | Viewed by 2178

Abstract

Although the idea of evaluating students’ mathematical knowledge with fuzzy logic is not new in the literature, few studies have explored the possibility of assessing students’ mathematical knowledge by combining teacher-assigned grades (i.e., school grades) with students’ achievements on standardized tests (e.g., national [...] Read more.

Although the idea of evaluating students’ mathematical knowledge with fuzzy logic is not new in the literature, few studies have explored the possibility of assessing students’ mathematical knowledge by combining teacher-assigned grades (i.e., school grades) with students’ achievements on standardized tests (e.g., national assessments). Thus, the present study aims to investigate the use of fuzzy logic to generate a novel assessment model, which combines teacher-assigned mathematics grades with students’ results on the Italian National Assessment of Mathematical Knowledge (INVALSI). We expanded the findings from previous works by considering a larger sample, which included more than 90,000 students attending grades 8, 10, and 13. The results showed that the tested model led to a lower assessment score compared to the traditional grading method based on teacher’s evaluation. Additionally, the use of fuzzy logic across the examined school levels yielded similar results, suggesting that the model is adequate among different educational levels. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

16 pages, 750 KiB

Open AccessArticle

Comparing Regional Attitudes toward Immigrants in Six European Countries

by Alessandro Indelicato, Juan Carlos Martín and Raffaele Scuderi

Axioms 2022, 11(7), 345; https://doi.org/10.3390/axioms11070345 - 19 Jul 2022

Cited by 7 | Viewed by 3036

Abstract

Many immigrants have risked their lives searching for a better future by crossing the Mediterranean Sea or the Atlantic Ocean. The Canary Islands became the centre of another emerging humanitarian and human rights crisis at Europe’s frontier in 2020. The study aims to [...] Read more.

Many immigrants have risked their lives searching for a better future by crossing the Mediterranean Sea or the Atlantic Ocean. The Canary Islands became the centre of another emerging humanitarian and human rights crisis at Europe’s frontier in 2020. The study aims to analyse whether attitudes towards immigrants are affected by territories close to these humanitarian crises. To this end, the study is based on previous studies using a Fuzzy-Hybrid TOPSIS method to analyse attitudes toward immigrants. The synthetic indicator will be built upon a set of eight indicators that proxy the ethnic, economic, cultural, and religious threats experienced by the citizens. The International Social Survey Program (ISSP) dataset for the year 2013 for six countries, namely Belgium, Germany, Spain, France, United Kingdom, and Portugal, will be used. Results show that the attitude toward immigrants is affected by the territorial dimension as classified by the nomenclature of territorial units for statistics at NUTS2 and NUTS3 levels, and that attitudes are very different between those of some of the archipelagos and islands considered in the study. In particular, our results point out a sort of duality between the Balearic Islands—the most open territory toward immigrants, and Corse—the least open territory toward immigrants. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

13 pages, 8351 KiB

Open AccessArticle

Interval Type-3 Fuzzy Aggregation of Neural Networks for Multiple Time Series Prediction: The Case of Financial Forecasting

by Oscar Castillo, Juan R. Castro and Patricia Melin

Axioms 2022, 11(6), 251; https://doi.org/10.3390/axioms11060251 - 26 May 2022

Cited by 30 | Viewed by 3277

Abstract

In this work, we present an approach for fuzzy aggregation of neural networks for forecasting. The interval type-3 aggregator is used to combine the outputs of the networks to improve the quality of the prediction. This is carried out in such a way [...] Read more.

In this work, we present an approach for fuzzy aggregation of neural networks for forecasting. The interval type-3 aggregator is used to combine the outputs of the networks to improve the quality of the prediction. This is carried out in such a way that the final output is better than the outputs of the individual modules. In our approach, a fuzzy system is used to estimate the prediction increments that will be assigned to the output in the process of combining them with a set of fuzzy rules. The uncertainty in the process of aggregation is modeled with an interval type-3 fuzzy system, which, in theory, can outperform type-2 and type-1 fuzzy systems. Publicly available data sets of COVID-19 cases and the Dow Jones index were utilized to test the proposed approach, as it has been stated that a pandemic wave can have an effect on the economies of countries. The simulation results show that the COVID-19 data does have, in fact, an influence on the Dow Jones time series and its use in the proposed model improves the forecast of the Dow Jones future values. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

17 pages, 667 KiB

Open AccessArticle

On the Factors of Successful e-Commerce Platform Design during and after COVID-19 Pandemic Using Extended Fuzzy AHP Method

by Dušan J. Simjanović, Nemanja Zdravković and Nenad O. Vesić

Axioms 2022, 11(3), 105; https://doi.org/10.3390/axioms11030105 - 26 Feb 2022

Cited by 9 | Viewed by 6008

Abstract

The ongoing COVID-19 pandemic has caused a paradigm shift in all aspects of contemporary human life. Everyday activities such as shopping have shifted from traditional methods to the ever-more growing online variants, allowing for an increase in electronic commerce (e-commerce) industry. As more [...] Read more.

The ongoing COVID-19 pandemic has caused a paradigm shift in all aspects of contemporary human life. Everyday activities such as shopping have shifted from traditional methods to the ever-more growing online variants, allowing for an increase in electronic commerce (e-commerce) industry. As more services become available online, consumers often rely on trusted services, which are often reflected on the web and mobile platforms they are presented on. In this paper, we study the factors for successful e-commerce platform design in the Western Balkans region using Fuzzy Analytical Hierarchy Process (FAHP) with triangular fuzzy numbers. After an extensive literature overview, interviews with representatives of top-ranking e-commerce companies in the region, and the analysis of experts’ opinions, we select a number of factors and sub-factors for prioritization, taking into account pre-pandemic factors, as well as the ones of the pandemic itself. We extend the FAHP model, which now consists of five (instead of three) points of view. Finally, we present and discuss the results in the form of tables and graphs, as well as an overall recommendation of what should be taken into account when designing an e-commerce platform. Our results rank service quality and security factors first and criteria such as multilingual support last. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

10 pages, 416 KiB

Open AccessArticle

The Relationships among Three Kinds of Divisions of Type-1 Fuzzy Numbers

by Yadan Jiang and Dong Qiu

Axioms 2022, 11(2), 77; https://doi.org/10.3390/axioms11020077 - 15 Feb 2022

Cited by 3 | Viewed by 2378

Abstract

The division operation for type-1 fuzzy numbers in its original form is not invertible for the multiplication operation. This is an essential drawback in some applications. To eliminate this drawback several approaches are proposed: the generalized Hukuhara division, generalized division and granular division. [...] Read more.

The division operation for type-1 fuzzy numbers in its original form is not invertible for the multiplication operation. This is an essential drawback in some applications. To eliminate this drawback several approaches are proposed: the generalized Hukuhara division, generalized division and granular division. In this paper, the expression of granular division is introduced, and the relationships among generalized Hukuhara division, generalized division and granular division are clarified. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

21 pages, 518 KiB

Open AccessArticle

Analyzing the Main Determinants for Being an Immigrant in Cuenca (Ecuador) Based on a Fuzzy Clustering Approach

by Juan Carlos Martin, Natalia Soledad Bustamante-Sánchez and Alessandro Indelicato

Axioms 2022, 11(2), 74; https://doi.org/10.3390/axioms11020074 - 14 Feb 2022

Cited by 5 | Viewed by 3072

Abstract

The study aims to analyze the determinants for being an immigrant in Cuenca (Ecuador). Our analysis is based on the answers given to a scale formed by 30 items included in a questionnaire administered to a representative sample of 369 immigrants. A fuzzy [...] Read more.

The study aims to analyze the determinants for being an immigrant in Cuenca (Ecuador). Our analysis is based on the answers given to a scale formed by 30 items included in a questionnaire administered to a representative sample of 369 immigrants. A fuzzy hybrid multi-criteria decision-making method, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), is used to analyze whether immigrants are more or less exigent regarding the items included in the scale to reside in Cuenca. Then, a fuzzy clustering method is applied to analyze the differences observed in the main determinants observed over a number of traits according to their similarities to three obtained profiles: (1) extreme exigent immigrants; (2) extreme unneedful immigrants; and (3) intermediate exigent immigrants. Results show that items such as access to internet and benefits for retirees were highly valued by some immigrants. In addition, the authors found that information channels, reasons for immigrating, house location, main transport mode, income and main income source are the main determinants that differentiate whether the immigrants in Cuenca (Ecuador) are more or less demanding with respect to the exigency scale developed in the study. The main contributions to the body of knowledge, the policy implications and lines for future research are finally discussed. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

25 pages, 3190 KiB

Open AccessArticle

Sustainable Integrated Fuzzy Optimization for Multimodal Petroleum Supply Chain Design with Pipeline System: The Case Study of Vietnam

by Chia-Nan Wang, Nhat-Luong Nhieu, Kim-Phong Tran and Yen-Hui Wang

Axioms 2022, 11(2), 60; https://doi.org/10.3390/axioms11020060 - 31 Jan 2022

Cited by 12 | Viewed by 4886

Abstract

Over the years, oil-related energy sources have played an irreplaceable role in both developed and developing countries. Therefore, the efficiency of petroleum supply chains is a key factor that significantly affects the economy. This research aimed to optimize the configuration of the uncertainty [...] Read more.

Over the years, oil-related energy sources have played an irreplaceable role in both developed and developing countries. Therefore, the efficiency of petroleum supply chains is a key factor that significantly affects the economy. This research aimed to optimize the configuration of the uncertainty multimodal petroleum supply chain in terms of economy, energy and environment (3E assessment). This study proposes a novel integration methodology between a heuristic algorithm and exact solution optimization. In the first stage, this study determines the facilities’ potential geographical coordinates using heuristic algorithm. Then, the fuzzy min-max goal programming model (FMMGPM) was developed to find the multi-objective solutions. In particular, this model allows analysis of supply chain uncertainty through simultaneous factors such as demand, resource, cost and price. These uncertainty factors are expressed as triangular fuzzy parameters that can be analyzed in terms of both probability and magnitude. Moreover, the model is applied to the entire petroleum supply chain in Vietnam, including downstream and upstream activities. In addition, another novelty is that for the first time, pipeline systems in logistics activities are considered in Vietnam’s petroleum supply chain optimization study. The results also show the short-term and long-term benefits of developing a pipeline system for oil transportation in Vietnam’s petroleum supply chain. To evaluate the effects of uncertainty on design decisions, this study also performed a sensitivity analysis with scenarios constructed based on different magnitudes and probabilities of uncertainty. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

13 pages, 1980 KiB

Open AccessArticle

A New Hybrid Triple Bottom Line Metrics and Fuzzy MCDM Model: Sustainable Supplier Selection in the Food-Processing Industry

by Nguyen Van Thanh and Nguyen Thi Kim Lan

Axioms 2022, 11(2), 57; https://doi.org/10.3390/axioms11020057 - 29 Jan 2022

Cited by 24 | Viewed by 4674

Abstract

Vietnam’s food processing and production industries in the past have managed to receive many achievements, contributing heavily to the growth of the country’s economic growth, especially the production index. Even with an increase of 7% per year over the past five years, the [...] Read more.

Vietnam’s food processing and production industries in the past have managed to receive many achievements, contributing heavily to the growth of the country’s economic growth, especially the production index. Even with an increase of 7% per year over the past five years, the industry currently also faces problems and struggles that require business managers to rewrite legal documents and redevelop the business environment as well as the production conditions in order to compete better and use the available resources. Xanthan gum (a food additive and a thickener) is one of the most used ingredients in the food-processing industry. Xanthan gum is utilized in a number of variety of products such as canned products, ice cream, meats, breads, candies, drinks, milk products, and many others. Therefore, in order to improve competitiveness, the stage of selecting raw-material suppliers is a complicated task. The purpose of this study was to develop a new composite model using Triple Bottom Line Metrics, the Fuzzy Analytical Hierarchy Process (FAHP) method, and the Combined Compromise Solution (CoCoSo) algorithm for the selection of suppliers. The application process was accomplished for the Xanthan-gum (β-glucopyranose (C₃₅H₄₉O₂₉)n) supplier selection in a food processing industry. In this study, the model building, solution, and application processes of the proposed integrated model for the supplier selection in the food-processing industry are presented. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

13 pages, 4368 KiB

Open AccessArticle

Brain Tumor Classification Using Dense Efficient-Net

by Dillip Ranjan Nayak, Neelamadhab Padhy, Pradeep Kumar Mallick, Mikhail Zymbler and Sachin Kumar

Axioms 2022, 11(1), 34; https://doi.org/10.3390/axioms11010034 - 17 Jan 2022

Cited by 112 | Viewed by 10732

Abstract

Brain tumors are most common in children and the elderly. It is a serious form of cancer caused by uncontrollable brain cell growth inside the skull. Tumor cells are notoriously difficult to classify due to their heterogeneity. Convolutional neural networks (CNNs) are the [...] Read more.

Brain tumors are most common in children and the elderly. It is a serious form of cancer caused by uncontrollable brain cell growth inside the skull. Tumor cells are notoriously difficult to classify due to their heterogeneity. Convolutional neural networks (CNNs) are the most widely used machine learning algorithm for visual learning and brain tumor recognition. This study proposed a CNN-based dense EfficientNet using min-max normalization to classify 3260 T1-weighted contrast-enhanced brain magnetic resonance images into four categories (glioma, meningioma, pituitary, and no tumor). The developed network is a variant of EfficientNet with dense and drop-out layers added. Similarly, the authors combined data augmentation with min-max normalization to increase the contrast of tumor cells. The benefit of the dense CNN model is that it can accurately categorize a limited database of pictures. As a result, the proposed approach provides exceptional overall performance. The experimental results indicate that the proposed model was 99.97% accurate during training and 98.78% accurate during testing. With high accuracy and a favorable F1 score, the newly designed EfficientNet CNN architecture can be a useful decision-making tool in the study of brain tumor diagnostic tests. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

► Show Figures

Figure 1

16 pages, 325 KiB

Open AccessArticle

Basic Core Fuzzy Logics and Algebraic Routley–Meyer-Style Semantics

by Eunsuk Yang

Axioms 2021, 10(4), 273; https://doi.org/10.3390/axioms10040273 - 25 Oct 2021

Cited by 1 | Viewed by 1486

Abstract

Recently, algebraic Routley–Meyer-style semantics was introduced for basic substructural logics. This paper extends it to fuzzy logics. First, we recall the basic substructural core fuzzy logic MIAL (Mianorm logic) and its axiomatic extensions, together with their algebraic semantics. Next, we introduce two kinds [...] Read more.

Recently, algebraic Routley–Meyer-style semantics was introduced for basic substructural logics. This paper extends it to fuzzy logics. First, we recall the basic substructural core fuzzy logic MIAL (Mianorm logic) and its axiomatic extensions, together with their algebraic semantics. Next, we introduce two kinds of ternary relational semantics, called here linear Urquhart-style and Fine-style Routley–Meyer semantics, for them as algebraic Routley–Meyer-style semantics. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

10 pages, 769 KiB

Open AccessArticle

On the Composition of Overlap and Grouping Functions

by Songsong Dai, Lei Du, Haifeng Song and Yingying Xu

Axioms 2021, 10(4), 272; https://doi.org/10.3390/axioms10040272 - 24 Oct 2021

Cited by 2 | Viewed by 1653

Abstract

Obtaining overlap/grouping functions from a given pair of overlap/grouping functions is an important method of generating overlap/grouping functions, which can be viewed as a binary operation on the set of overlap/grouping functions. In this paper, firstly, we studied closures of overlap/grouping functions w.r.t. [...] Read more.

Obtaining overlap/grouping functions from a given pair of overlap/grouping functions is an important method of generating overlap/grouping functions, which can be viewed as a binary operation on the set of overlap/grouping functions. In this paper, firstly, we studied closures of overlap/grouping functions w.r.t. ⊛-composition. In addition, then, we show that these compositions are order preserving. Finally, we investigate the preservation of properties like idempotency, migrativity, homogeneity, k-Lipschitz, and power stable. Full article

(This article belongs to the Special Issue Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences)

Journal Menu

Journal Browser

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (14 papers)

Editorial

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI