Journal of Fuzzy Extension and Applications
http://www.journal-fea.com/
Journal of Fuzzy Extension and Applicationsendaily1Fri, 01 Jul 2022 00:00:00 +0430Fri, 01 Jul 2022 00:00:00 +0430Using a combined fuzzy-AHP and topsis decision model for selecting the best firewall alternative
http://www.journal-fea.com/article_141557.html
Covid-19 pandemic forced all the world to make significant changes in their daily routines. As a result, internet and digital technologies started to be used more actively by individuals and businesses. Due to this digitalization, everyone is more open to digital threats. In order to provide the security of the network, firewalls should be used. Firewalls act as a barrier between the internal and the external networks. Thus, it is more important than ever to choose the right firewall for each network. In this study, an integrated Fuzzy-Analytic Hierarchy Process (AHP) and TOPSIS model is introduced to find out the most suitable firewall. A survey is designed and used to generate the data of this study. This study distinguishes from other studies by proposing a solution which ranks the firewall alternatives using a combination of fuzzy-AHP and TOPSIS models. As a result, among the five different firewall alternatives, the second one is found out to be the best. A solution proposal ranking the firewall alternatives is new in the literature. This approach is used in many different Multi-Criteria Decision Making (MCDM) problems before but not in firewall selection. Hence, this study can be considered quite innovative in terms of the problem it handles and the model used. It offers a new solution related to a decision making problem that has started to gain more importance with the current digitalization process due to Covid-19 pandemic.Evaluation of key impression of resilient supply chain based on artificial intelligence of things (AIoT)
http://www.journal-fea.com/article_151126.html
In recent years, the high complexity of the business environment, dynamism and environmental change, uncertainty and concepts such as globalization and increasing competition of organizations in the national and international arena have caused many changes in the equations governing the supply chain. In this case, supply chain organizations must always be prepared for a variety of challenges and dynamic environmental changes. One of the effective solutions to face these challenges is to create a resilient supply chain. Resilient supply chain is able to overcome uncertainties and disruptions in the business environment. The competitive advantage of this supply chain does not depend only on low costs, high quality, reduced latency and high level of service. Rather, it has the ability of the chain to avoid catastrophes and overcome critical situations, and this is the resilience of the supply chain. AI and IoT technologies and their combination, called AIoT, have played a key role in improving supply chain performance in recent years and can therefore increase supply chain resilience. For this reason, in this study, an attempt was made to better understand the impact of these technologies on equity by examining the dimensions and components of the Artificial Intelligence of Things (AIoT)-based supply chain. Finally, using nonlinear fuzzy decision making method, the most important components of the impact on the resilient smart supply chain are determined. Understanding this assessment can help empower the smart supply chain.The fuzzy subgroups for the nilpotent ( p-group) of (d23 × c2m) for m ≥ 3
http://www.journal-fea.com/article_152027.html
A group is nilpotent if it has a normal series of a finite length n. By this notion, every finite p-group is nilpotent. The nilpotence property is an hereditary one. Thus, every finite p-group possesses certain remarkable characteristics. In this paper, the explicit formulae is given for the number of distinct fuzzy subgroups of the Cartesian product of the dihedral group of order 23 with a cyclic group of order of an m power of two for, which m &ge; 3.Age and gender classification from facial features and object detection with machine learning
http://www.journal-fea.com/article_148293.html
In recent years, development of the machine learning algorithms has led to the creation of intelligent surveillance systems. Thanks to the machine learning, it is possible to perform intelligent surveillance by recognizing people's facial features, classifying their age and gender, and detecting objects around instead of ordinary surveillance. In this study, a novel algorithm has been developed that classifies people's age and gender with a high accuracy rate. In addition, a novel object recognition algorithm has been developed that detects objects quickly and with high accuracy. In this study, age and gender classification was made based on the facial features of people using Convolutional Neural Network (CNN) architecture. Secondly, object detection was performed using different machine learning algorithms and the performance of the different machine learning algorithms was compared in terms of median average precision and inference time. The accuracy of the age and gender classification algorithm was tested using the Adience dataset and the results were graphed. The experimental results show that age and gender classification algorithms successfully classify people's age and gender. Then, the performances of object detection algorithms were tested using the COCO dataset and the results were presented in graphics. The experimental results stress that machine learning algorithms can successfully detect objects.Decision-making analysis of minimizing the death rate due to covid-19 by using q-rung orthopair fuzzy soft bonferroni mean operator
http://www.journal-fea.com/article_152026.html
The q-Rung Orthopair Fuzzy Soft Set (q-ROFSS) theory is a significant extension of Pythagorean fuzzy soft set and intuitionistic fuzzy soft set theories for dealing with the imprecision and uncertainty in data. The purpose of this study is to improve and apply this theory in decision-making. To achieve this purpose, we firstly propose some Bonferroni Mean (BM) and Weighted Bonferroni Mean (WBM) aggregation operators for aggregating the data. Some desired properties are presented in detail and the existing aggregation operators are used as distinct cases of our proposed operators. Further, a decision-making analysis is presented based on our proposed operations and applied to decision-making in COVID-19 diagnosis. The preferred way is discussed to protect maximum human lives from COVID-19. A numerical example is given to support the claim. The experimental results demonstrate the proposed operators have an ability to make a precise decision with imprecision and uncertain information which will find a broad application in the decision-making area.An efficient parallel greedy algorithm for fuzzy hybrid flow shop scheduling with setup time and lot size: a case study in apparel process
http://www.journal-fea.com/article_141668.html
This paper deals with the Fuzzy Hybrid Flow Shop (FHFS) scheduling inspired by a real apparel process. A Parallel Greedy (PG) algorithm is proposed to solve the FHFS problems with Setup Time (ST) and Lot Size (LS). The fuzzy model is used to define the uncertain setup and Processing Time (PT) and Due Dates (DDs). The setup and PTs are defined by a Triangular Fuzzy Number (TAFN). Also, the Fuzzy Due Date (FDD) is denoted by a doublet. The tardiness, the tardy jobs, the setup and Idle Time (IT), and the Total Flow (TF) time are minimized by the proposed PG algorithm. The effectiveness of the proposed PG algorithm is demonstrated by comparing it with the Genetic Algorithm (GeA) in the literature. A real-world application in an apparel process is done.&nbsp; According to the results, the proposed PG algorithm is an efficient method for FHFS scheduling problems with ST and LS in real-world applications.Prioritisation of GPM activities from lean-agile-resilience perspective using fuzzy analytic hierarchy process
http://www.journal-fea.com/article_148898.html
Green Project Management (GPM) involves a set of management actions to identify and evaluate the impact of activities on the environment and to control and improve performance. Accordingly, the concepts of lean, agility and resilience have a special place as driving forces because they can play an important role in improving the environment. Therefore, the present study is conducted with the aim of identifying and prioritizing GPM activities. They are introduced based on the principles of project management knowledge set and considering the concept of green. Then, by considering the concepts of resilience, agility and purity as research criteria using Fuzzy Analytic Hierarchy Process (FAHP), activities are prioritized. This study has a pairwise comparison questionnaire that data are collected from construction industry experts. The incompatibility rate index is used to determine the reliability of the questionnaire. The results show that the five activities of GPM are identifying a team that can align the project with environmental policies. Development, documentation of the project charter, setting goals in the project charter, quality control, cost, planning, safety of environmental activities, and preparation of GPM &nbsp;programs, respectively, should be given more attention.FUZZY METRIC TOPOLOGY SPACE AND MANIFOLD
http://www.journal-fea.com/article_150211.html
This paper, considers the fuzzy topological subsets, fuzzy topological spaces and introduces a novel concept of fuzzy Hausdorff space and fuzzy manifold space in this regards. Based on these concepts, we present a concept of fuzzy metric Hausdorff spaces and fuzzy metric manifold spaces via the notations of KM-fuzzy metric spaces.This study, generalises the concept of fuzzy metric space to union and product of fuzzy metric spaces in classical logic and in this regard investigates the some product of fuzzy metric fuzzy manifold spaces. We apply the notation of valued-level subsets and make a relation between of topological space, Husdorff space, manifold space and fuzzy topological space, fuzzy Husdorff space and fuzzy manifold space. In final, we extended the fuzzy topological space, fuzzy Husdorff space and fuzzy manifold space to fuzzy metric topological space, fuzzy metric Husdorff space and fuzzy metric manifold spaceIndeed, this study analyses the notation of fuzzy metric manifold based on valued-level subset.Basic fuzzy arithmetic operations using α–cut for the Gaussian membership function
http://www.journal-fea.com/article_153240.html
Currently fuzzy set theory has a wide range to model real life problems with incomplete or vague information which perfectly suits the reality and its application is theatrically increasing. This study explored the basic fuzzy operations with the Gaussian Membership using the &alpha;-cut method. As it is known that, the Gaussian membership function has a great role in modelling the fuzzy problems this is what impelled to explore its operation which can further be used in analysis of fuzzy problems. The use of Gaussian Membership function add more realist compartment to investigate each elements behavior and its predication outputs. Graphical analysis has been done for each operation depicting the results of the corresponding operation to the original membership function(s). Primarily the basic operations which has been discussed here are addition, subtraction, multiplication, division, reciprocal, exponential, logarithmic and nth power.The sightseen operations can further be used in analysis of fuzzy sets with Gaussian Membership and using the alpha-cut method to make things easier for the calculations of all the basic operations. Therefore, we propose this approach to be used when analyzing the fuzzy problem with Gaussian MembershipFuzzy Cognitive Study On Post Pandemic Impact On Occupational Shift In Rural Areas
http://www.journal-fea.com/article_154421.html
The pandemic has created a wide range of impacts on the livelihood of the people especially in their occupation and income generation. The horrific pandemic impacts have caused the populace to switch their occupations for the sake of their livelihood sustainability. This research works aims in determining the impacts of the occupational shifts especially in case of rural populace. The decision-making method of Fuzzy Cognitive maps (FCM) is used in combinations with the statistical data collection methods of survey methodology, participatory approach and multi stage purposive sampling. It is observed that a significant percentage of people have shifted from their occupation and the occupational shifts have impacts on the personal, economic, social and health dimensions of the rural populace. The factors under each dimension and their inter associational impacts are also determined using the method of FCM and FCM Expert software. Based on the findings of the research work, it is very evident that the occupational shifts have created a lot of impacts on the livelihood of the rural populace and also each of the person has experienced the impacts more personally. The societal contribution of the research lies in communicating the results and inferences to the concerned administrators so as to facilitate the affected rural populace in getting back to their primary occupation.Some Picture Fuzzy Mean Operators and their Applications in Decision Making
http://www.journal-fea.com/article_154621.html
Picture fuzzy set is the generalization of fuzzy set and intuitionistic fuzzy set. It is useful for handling uncertainty by considering positive membership, neutral membership and the negative membership degrees independently for each element of a universal set. The main objective of this article is to develop some picture fuzzy mean operators, including Picture Fuzzy Harmonic Mean (PFHM), Picture Fuzzy Weighted Harmonic Mean (PFWHM), Picture Fuzzy Arithmetic Mean (PFAM), Picture Fuzzy Weighted Arithmetic Mean (PFWAM), Picture Fuzzy Geometric Mean (PFGM) and Picture Fuzzy Weighted Geometric Mean (PFWGM), to aggregate the picture fuzzy sets. Moreover, we discuss some relevant properties of these operators. Furthermore, we apply these mean operators to make decision with practical examples. Finally, to show the efficiency and the validity of the proposed operators, we compare our results with the results of existing methods and concluded from the comparison that our proposed methods are more effective and reliable.Detection of counterfeit banknotes using Genetic Fuzzy System
http://www.journal-fea.com/article_154622.html
Due to developments in printing technology, the number of counterfeit banknotes is increasing every year. Finding an effective method to detect counterfeit banknotes is an important task in business. Finding a reliable method to detect counterfeit banknotes is a crucial challenge in the world of economic transactions. Due to technological development, counterfeit banknotes may pass through the counterfeit banknote detection system based on physical and chemical properties undetected. In this study, an intelligent counterfeit banknote detection system based on a Genetic Fuzzy System (GFS) is proposed to detect counterfeit banknotes efficiently. GFS is a hybrid system that uses a network architecture to fine-tune the membership functions of a fuzzy inference system. The learning algorithms Fuzzy Classification, Genetic Fuzzy Classification, ANFIS Classification, and Genetic ANFIS Classification were applied to the dataset in the UCI machine learning repository to detect the authenticity of banknotes. The developed model was evaluated based on Accuracy (ACC), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Error Mean, Error STD, and confusion matrix. The experimental results and statistical analysis showed that the classification performance of the proposed model was evaluated as follows: Fuzzy = 97.64%, GA_Fuzzy = 98.60%, ANFIS = 80.83%, GA_ANFIS = 97.72% accuracy (ACC). This shows the significant potential of the proposed GFS models for fraud detection.Fuzzy Simple Linear Regression Using Gaussian membership functions Minimization problem
http://www.journal-fea.com/article_155107.html
Under the additional assumption that the errors are normally distributed, the ordinary least squares method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the ordinary least squares method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the Employment Poverty relationship.
Under the additional assumption that the errors are normally distributed, the ordinary least squares method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the ordinary least squares method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the Employment Poverty relationship.Supply Chain Management Problem Modelling in Hesitant fuzzy environment
http://www.journal-fea.com/article_155277.html
Complex nature of the current market is often caused by uncertainties, data uncertainties, their manner of use, and differences in managers&#039; viewpoints. To overcome these problems, hesitant fuzzy sets (HFSs) can be useful as the extension of fuzzy set theory, in which the degree of membership of an element can be a set of possible values and provide greater flexibility in design and, thus, model performance. The power of this application becomes clear when different decision-makers tend to independently record their views. We know that there are usually several goals for managers to achieve the desired performance. Therefore, in this study, firstly a description of the solution of the hesitant fuzzy linear programming problem (HFLP) for solving hesitant fuzzy multi-objective problems is considered. In the following, the multi-objective and three-level supply chain management problem is modeled with the hesitant fuzzy approach. Then, with an example, high flexibility of the model responses is evaluated by the proposed method. Under different circumstances with appropriate modifications, it is possible to extend the hesitant fuzzy model presented in this study to other supply chain management problems.A note on somewhat fuzzy continuity
http://www.journal-fea.com/article_157842.html
Thangaraj and Balasubramanian introduced the so-called somewhat fuzzy semicontinuous and somewhat fuzzy semiopen functions. Two years later, the same authors defined two other types of functions called somewhat fuzzy continuous and somewhat fuzzy open without indicating connections between them. At first glance, we may easily conclude (from their definitions) that every somewhat fuzzy continuous (resp. open) function is somewhat fuzzy semicontinuous (resp. semiopen) but not conversely. In this note, we show that they are equivalent. We further prove that somewhat fuzzy continuous functions are weaker than fuzzy semicontinuous functions.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -- - - - -- - - - - - - - - - - - - - - - - - - - - - - - -Soft Set Product extended to HyperSoft Set and IndetermSoft Set Product extended to IndetermHyperSoft Set
http://www.journal-fea.com/article_157982.html
In this paper we define the Soft Set Product as a product of many soft sets and afterwards by their intersection into a HyperSoft Set. Similarly, the IndetermSoft Product is extended be intersection to the IndetermHyperSoft Set. We also present several applications of the Soft Set Product to Fuzzy (and fuzzy-extensions) Soft Set Product and to IndetermSoft Set and IndetermHyperSoft Set.