Fuzzy Multi Research Articles

Fuzzy Multi Attribute Decision Making Determining House DSS

The property industry in Indonesia is experiencing rapid development along with improving economic conditions, causing consumers to face difficulties in choosing a house that suits their preferences. Various factors such as price, location, facilities, and payment methods often make decisions complex. The Fuzzy Multi Attribute Decision Making (FMADM) method is used to determine and evaluate the best options based on the degree of suitability of all criteria, with ranking carried out using the defuzzy method. The results of this study are expected to provide practical solutions for consumers in choosing a house that suits their needs and improve the quality of property developer services in Indonesia. The author's test results show that 72% of users feel helped by this solution method.

An Adaptive Multi-Stage Fuzzy Logic Framework for Accurate Detection and Structural Analysis of Road Cracks

An Adaptive Multi-Stage Fuzzy Logic Framework for Accurate Detection and Structural Analysis of Road Cracks

Risk assessment of organ transplant operation: A fuzzy hybrid MCDM approach based on fuzzy FMEA.

Nowadays, most fatal diseases are attributed to the malfunction of bodily. Sometimes organ transplantation is the only possible therapy, for instance for patients with end-stage liver diseases, and the preferred treatment, for instance for patients with end-stage renal diseases. However, this surgical procedure comes with inherent risks and effectively managing these risks to minimize the likelihood of complications arising from organ transplantation (maximizing life years from transplant and quality-adjusted life years) is crucial. To facilitate this process, risk ranking is used to identify and promptly address potential risks. Over recent years, considerable efforts have been made, and various approaches have been proposed to enhance Failure Modes and Effects Analysis (FMEA). In this study, taking into account the uncertainty in linguistic variables (F-FMEA), we introduce an approach based on Fuzzy Multi Criteria Decision Making (F-MCDM) for effectively evaluating scenarios and initial failure hazards. Nevertheless, the results of ranking failure modes generated by different MCDM methods may vary. This study is a retrospective study that suggests a comprehensive unified risk assessment model, integrating multiple techniques to produce a more inclusive ranking of failure modes. Exploring a broad spectrum of risks associated with organ transplant operations, we identified 20 principal hazards with the assistance of literature and experts. We developed a questionnaire to examine the impact of various critical factors on the survival of transplanted organs, such as irregularities in immunosuppressive drug consumption, inappropriate dietary habits, psychological disorders, engaging in strenuous activities post-transplant, neglecting quarantine regulations, and other design-related factors. Subsequently, we analyzed the severity of their effects on the durability of transplanted organs. Utilizing the Mamdani algorithm as a fuzzy inference engine and the Center of Gravity algorithm for tooling, we expressed the probability and severity of each risk. Finally, the failure mode ranking obtained from the F-FMEA method, three fuzzy MCDM methods, and the proposed combined method were identified. Additionally, the results obtained from various methods were evaluated by an expert team, demonstrating that the highest consistency and effectiveness among different methods are attributed to the proposed method, as it achieved a 91.67% agreement with expert opinions.

Computational Solution and Analysis of Fuzzy Nonlinear HIV Infection Model via New Multistage Fuzzy Variational Iteration Method

Computational Solution and Analysis of Fuzzy Nonlinear HIV Infection Model via New Multistage Fuzzy Variational Iteration Method

Assessment of polluted region using an integrated weighting approach and fuzzy VIKOR method

Air pollution exerts a profound impact on both public health and the natural environment. In India, festivals like Diwali also contaminate the air by releasing pollutants into the atmosphere. It is essential to identify the most polluted region by estimating these pollutants. Since air quality assessment involves multiple air pollutants, there may be inherent uncertainty associated with data. This study employs a fuzzy Multi Attribute Decision Making (MADM) framework fuzzy Analytical Hierarchy Process-Entropy-fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FAHP-Entropy-FVIKOR) to model the impact of air pollution as a decision-making problem to address the uncertainty and assess the air quality during the Diwali festival from 2019 to 2021 in Tamil Nadu, India. An integrated weighting approach is utilised to determine the weights of the air pollutants using a fuzzy Analytical Hierarchy Process and Entropy methods. Mainly, the fuzzy VIKOR approach is employed to rank the polluted regions. The validation of the proposed model is established through a comparative analysis using Spearman’s rank correlation with two other existing fuzzy MADM methods. Furthermore, a sensitivity analysis is conducted to evaluate the influence of priority weights and the interdependence of pollutants in determining regional rankings. The results conclude that a strong positive correlation is attained between the proposed and existing methods and the highest levels of air pollution during the festival period are observed in Gandhi Nagar (2019), Rayapuram (2020), T. Nagar, Sowcarpet and Triplicane (2021) in their respective years. These findings substantiate the consistency and effectiveness of the proposed approach.

Penerapan Metode Fuzzy Multi Criteria Decision Making Pada Interpretasi Hasil Penentuan Kemiskinan Provinsi Jawa Timur

Fuzzy Multi Criteria Decision Making (FMCDM) method is a method of making decisions based on certain criteria to determine the best alternative among several alternatives. The purpose of the FMCDM method is to obtain the best alternative that is accurate and optimal. Poverty is a condition in which economic needs are not met against the average standard of living in the region. Poverty is a very important issue for the government or related agencies. This problem can be solved by determining the district/city area which is included in the poor category. So a method is needed that can be used to determine the existence of poverty in an area. The solution to overcome this problem is to use the FMCDM method. The solution to overcome this problem is to use the FMCDM method. The FMCDM process begins by determining objectives, alternative decisions, and a collection of criteria that will be used to determine poor districts/cities in East Java Province. The alternative decisions consist of 38 regencies/cities of East Java Province, while the set of criteria consists of the Percentage of Poor People, Human Development Index, Poverty Depth Index, and Poverty Severity Index. The next step evaluates the fuzzy set by aggregating the weight of the criteria and the degree of fit of each alternative to its criteria. The aggregation result is called the fuzzy match index which consists of three values, namely, the value which represents the result of the lower limit aggregation, the value which represents the middle bound, and the value which represents the upper bound value. The three values are ranked using the ranking method for fuzzy numbers with degrees of optimasan. So that the total integral value for each alternative will be a decision from the highest priority to the lowest in determining the districts / cities included in the poor category and as an effort to reduce poverty in East Java Province.

Penentuan Peringkat Penilaian Kinerja Pegawai Sebagai Pendukung Keputusan Menggunakan Metode Fuzzy Elimination Et Choix Traduisant La Realite

This study discusses the Fuzzy Elimination Et Choix Traduisant La Realite (ELECTRE) method that can be applied to make a decision support. This method was chosen because it is one of the methods used to rank and determine the best alternative. This study aims to determine the results of the application of the fuzzy ELECTRE method which produces alternative solutions in determining employee performance appraisal ratings for the Education and Culture Office of Malang City. Some of the problems that often occur in employee performance evaluation at the Department of Education and Culture in the city of Malang are still ineffective and inaccurate because the calculation process is still manual. Based on this, the effort to reduce the problems above is to implement a Fuzzy Multi Attribute Decision Making decision support system with the fuzzy ELECTRE method. This method requires a process of normalizing the decision matrix (X) into a comparable scale, then weighting the normalized matrix, then determining the concordance and discordance indices for each alternative pair to calculate the concordance and discordance indices, the ranking process is used to choose the best alternative. This study is limited by several criteria used as linguistic variables with the Triangular Fuzzy Number scale, including SKP scores, service orientation, integrity, commitment, discipline, and cooperation. Based on employee performance appraisal data that has been calculated using the fuzzy ELECTRE method, the best alternative that occupies the top rank with the highest value is alternative 2 with a value of 55.9155. It is hoped that by using the fuzzy ELECTRE method, the ranking process can be more precise in identifying employees who will become outstanding employees.

Sustainable energy transition in Southeast Asia: Energy status analysis, comprehensive evaluation and influential factor identification

Southeast Asia, one of the world's most vibrant economies, faces significant challenges in enhancing energy security and mitigating carbon emissions. This study provides a holistic view of the energy security status in Southeast Asia by presenting energy facts from six aspects and identify the critical factors affecting sustainable energy transition in this region with the techniques of political, economic, social, technological, environmental, and legal (PESTEL) Analysis and fuzzy Multi Criteria Decision Making (MCDM) methods. It indicates that: (1) Southeast Asia performs well in enhancing energy supply but awkwardly in sustainable energy transition, and great divergence exists among different countries; (2) The economic aspect is the most important in sustainable energy transition, followed by the technological, environmental and political aspects; (3) Important factors influencing sustainable energy transition in Southeast Asia include political instability, backward economy, uncertain social acceptance, insufficient energy infrastructure, restrictions of geographical conditions, and limited government efforts.

The Multistage Fuzzy Logic-Based Decision Support Model to Determine the Salary of New Employees

The Multistage Fuzzy Logic-Based Decision Support Model to Determine the Salary of New Employees

Penerapan Metode Fuzzy Simple Additive Weigting Pada Interpretasi Hasil Penilaian Promosi Jabatan Pegawai Negeri Sipil

The Fuzzy Simple Additive Weighting (FSAW) method is a mechanism that can be used to support decision making. This method was chosen because a ranking process was carried out to determine the weight value of each attribute, which would select employees who were worthy of occupying the promoted position. This study aims to determine the results of the application of the FSAW method in the assessment of civil servant promotion at the Malang City Education and Culture Office to increase objectivity and fairness in the assessment of employee promotion. Some problems that often occur in employee evaluation are the employee evaluation process which is still conventional so that it is less effective in calculation. The solution to overcome this problem is to use a Fuzzy Multi Attribute Decision Making (FMADM) decision support system with the FSAW method. This method requires a process to normalize the decision matrix (X) against a scale that can be compared with all available alternative values. After each attribute has been determined its weight value, the ranking process is used to select the best alternative for this study. The criteria used in this decision support system are SKP score, length of service, class, and education. The membership function used is the Triangular Fuzzy Number (TFN) representation. The results of the ranking calculation or the best value show the highest value, namely 1 from alternative 1 (employee 1) who is entitled to a promotion. It is expected that by using the FSAW method, the task of selectors will be able to more quickly and precisely identify employees who are worthy of occupying positions promoted based on the desired conditions.

SPACED REPETITION CONCEPT DESIGN WITH FUZZY MULTI CRITERIA ANALYSIS AS A MEDIA TO IMPROVE NUMERACY LEARNING FOR ELEMENTARY SCHOOL STUDENTS

Numeracy Learning activities after the Covid-19 Pandemic has been decline in the quality of learning in a number of elementary school students. This research is limited to learning numeracy for low grade students, namely grade 1,2, and 3, because the basic concept of numeration begins with low grades There are several factors that make difficult for students to understand numeracy, the students often forget about the concepts that have been taught before. An Effective way of memorizing with the conventional way is memorizing with repeat pronunciations. To improve the quality of education, learning concepts that were previously carried out conventionally must be developed in a modern way using application. The purpose of this research is to improve the numeracy learning concept of low-grade students in primary school after Covid-19 pandemic which is more fun and modern by using the concept of spaced repetition based on android flashcards. The analysis of 135 student’s assessment is based on criteria such as tangible, reliability, empathy, responsive, and assurance. The decision support system using Fuzzy Multi Criteria Methods (MCDM) is also used to determine the weighting of the criteria and the effectiveness of learning using spaced repetition concept and it’s application. The result of the weighting using fuzzy multi criteria is obtained defuzzification that tangible 65.18, reliability 56.54, responsive 46.17, assurance 49.13, and empathy 29.62. Tangible has the highest results in this test, it means that the students prefer modern learning with android application with an attractive experienced. The correlation test obtained the result 0.76 which is a high value in decision making and could be accepted.

A knowledge-based decision support system for incident traffic congestion management

A Knowledge-based Decision Support System (KB-DSS) based on a multi-stage Fuzzy Logic Controller (MS-FLC) is developed for traffic congestion management on expressways. The MS-FLC receives real-time traffic and incident data to analyse and anticipate the traffic conditions, to recommend alternative control measures in the form of natural languages for the human operator to select control decisions, and to calculate control settings to manage traffic congestion. In a case study, the KB-DSS is evaluated on a simulated network in comparison to ALINEA\Q, a popular ramp control method, across various traffic and incident situations. The results showed that: (i) the KB-DSS provides a systematic procedure in deriving control actions and a good capability to deliver linguistic expressions; (ii) the KB-DSS outperforms ALINEA\Q with respect to global objectives across many scenarios, attains significant improvements of mainline travel conditions and substantial reductions of ramp queues. These advantages make the KB-DSS a robust tool for traffic control for incident congestion management on expressways.

Site Suitability Analysis for Potential Eco-Tourism Sites with Fuzzy Multi Criteria Decision Analysis in Nashik District

Site Suitability Analysis for Potential Eco-Tourism Sites with Fuzzy Multi Criteria Decision Analysis in Nashik District

(α, γ)-Anti-Multi-Fuzzy Subgroups and Some of Its Properties

Recently, fuzzy multi-sets have come to the forefront of scientists’ interest and have been used in algebraic structures such as multi-groups, multi-rings, anti-fuzzy multigroup and (α, γ)-anti-fuzzy subgroups. In this paper, we first summarize the knowledge about the algebraic structure of fuzzy multi-sets such as (α, γ)-anti-multi-fuzzy subgroups. In a way, the notion of anti-fuzzy multigroup is an application of anti-fuzzy multi sets to the theory of group. The concept of anti-fuzzy multigroup is a complement of an algebraic structure of a fuzzy multi set that generalizes both the theories of classical group and fuzzy group. The aim of this paper is to highlight the connection between fuzzy multi-sets and algebraic structures from an anti-fuzzification point of view. Therefore, in this paper, we define (α, γ)-anti-multi-fuzzy subgroups, (α, γ)-anti-multi-fuzzy normal subgroups, (α, γ)-anti-multi-fuzzy homomorphism on (α, γ)-anti-multi-fuzzy subgroups and these been explicated some algebraic structures. Then, we introduce the concept (α, γ)-anti-multi-fuzzy subgroups and (α, γ)-anti-multi-fuzzy normal subgroups and of their properties. This new concept of homomorphism as a bridge among set theory, fuzzy set theory, anti-fuzzy multi sets theory and group theory and also shows the effect of anti-fuzzy multi sets on a group structure. Certain results that discuss the (α, γ) cuts of anti-fuzzy multigroup are explored.

HUMAN RESOURCES MANAGER SELECTION BASED ON FUZZY AND INTUITIONISTIC FUZZY NUMBERS FOR LOGISTICS COMPANIES

Qualified managers are needed for the systematic functioning of logistics management applications. In logistics companies, the human resources manager takes part in determining the amount of personnel needed, supplying personnel, and creating personnel task forms. For successful human resources management, a qualified human resources manager should be selected. In the literature, it is seen that the manager selection problem is handled with multi criteria decision making (MCDM) methods. The aim of this research is to determine the problem criteria of human resources manager selection for logistics companies and to apply them with hybrid MCDM methods. With the in-depth literature review, ten criteria were determined for the logistics company human resources manager selection problem. The intuitionistic fuzzy weighted averaging (IFWA) method was used to weight the criteria. The fuzzy multi attribute ideal-real comparative analysis (F-MAIRCA) method was applied for the ranking of the four candidate managers. The application was made on a logistics company operating in Turkey. Research methods are based on fuzzy and intuitionistic fuzzy numbers. As a result of the study, the most important criterion in the selection of logistics human resources manager was determined as the experience criterion. Among the four candidates, the first candidate was seen as the best manager candidate. Suggestions have been developed for logistics companies, human resources manager candidates and researchers based on the research outputs. In addition, with this research, the IFWA and F-MAIRCA hybrid method has been brought to the literature.

Detected The Sex Of Fish That Is Good For Cultivation Using Fuzzy

Fish is a type of vertebrate animal that is poikilotermic (cold-blooded), has distinctive features on its spine, gills and fins and depends on water as a medium for life. Fish have the ability in the water to move by using fins to maintain the balance of their body so that it does not depend on the current or movement of water caused by the wind direction using the FMADM (fuzzy multi attribute decision making) method. The purpose of this study is to get the problem to be solved, namely making a decision support model using the FMADM (fuzzy multi attribute decision making) method with the help of image processing in determining the sex of fish to increase fish farming yields. The preferred alternative in the selection of fish sex is that the 4th alternative has the highest value as the best prospective fish brood with a weighting point of 0.57. Then the investigation is carried out using image processing which is processed using photoshop so that it can be calcified into three image creteria of the physical shape of the sex, and from the number of spines located on the fins of the fish.

Classifying environmental significance levels of production-oriented operational activities with F-ARAS and F-MOORA methods.

In most decision analysis approaches, application results are obtained in the form of a ranking or selection set. However, classificationis needed for analysis of results. In this study, "environmental significance levels and range values" were created for the ranking results obtained using fuzzy Multi Criteria Decision Making approaches. Environmental significance levels have been established for 26 operational activities for which environmental impacts have been determined. Operational activities were analyzed using the Fuzzy-Additive Ratio Assessment (F-ARAS), Fuzzy-Multi Objective Optimization by Ratio Analysis (F-MOORA) Ratio,and F-MOORA Reference Point methods with sixevaluation criteria, including the total impact score criteria. The results obtained were analyzed with "environmental significance levels and range values," which can also be named as environmental risk classes created for the first time in this study depending on the changes in standard deviation. According to the comparison results, when F-ARAS and F-MOORA Ratio methods were evaluated together, 19 activities were in the same class (73%). Integr Environ Assess Manag 2023;19:763-774. © 2022 SETAC.

A Novel Operator to Solve Decision-Making Problems Under Trapezoidal Fuzzy Multi Numbers and Its Application

This article investigates solutions to multiple attribute decision-making (MADM) problems in which the attribute values take the form of trapezoidal fuzzy multi-numbers. To do this, this paper proposes a kind of mean aggregation operator called the Bonferroni harmonic mean operator for aggregating trapezoidal fuzzy information. Then, an approach that is a solution algorithm has been developed to find a solution to multi-attribute decision-making problems. Afterwards, an illustrative example has been given to verify the developed approach and to show its usefulness and efficiency. Finally, a comparison table has been presented to compare the proposed method with some existing methods.

Picture Fuzzy Choquet Integral Based Geometric Aggregation Operators and Its Application to Multi Attribute Decision-Making

Picture fuzzy set is an extension of intuitionistic fuzzy set, which allows interpreting uncertain data in decision-making problems. This study provides aggregation operators based on Choquet integral, namely Choquet integral picture fuzzy geometric aggregation (CIPFGA) operator and Choquet integral picture fuzzy hybrid geometric aggregation (CIPFHGA) operator with certain properties of these operators are established. We validate the functioning of the operators with illustrative examples. The CIPFHGA operator has an added benefit of combining the weights of positions along with capturing the comprehensive correlative relationships of the criteria. Further, the proposed operators enable us to solve a numerical problem in picture fuzzy Multi attribute decision-making problem and also allows to make a comparison study with the existing literature.

A Multi-Stage Fuzzy Model for Assessing Applicants for Faculty Positions in Universities

Assessing applicants for faculty positions in universities involves many issues. Each issue may involve a judgment based on uncertain or imprecise data. The uncertainty in data may exist in the interpretation made by the evaluator. This issue might lead to improper decision making. Modeling such a system using fuzzy logic will provide a more efficient model for handling imprecision. This article presents a fuzzy system for modeling the assessment of applicants for employment at academic universities. This system will utilize a multi-stage fuzzy model for measuring and evaluating the applicants. Utilizing fuzzy logic for applicants' evaluation will help administrators in choosing the best candidates for faculty positions. The fuzzy system was developed using jFuzzyLogic Java library. The reliability of the proposed system was proved by evaluating real-world case studies to prove its effectiveness to mimic human judgment. Moreover, the developed system has been evaluated by comparing it with a traditional mathematical method to prove the credibility and fairness of the proposed fuzzy system.