Fuzzy Scale Research Articles

Selection of Desalination System for Commercial Vessels by Implementing Improved Intuitionistic Fuzzy TOPSIS Method

The process of desalination of seawater on commercial vessels is a vital event in the daily life of the crew. As a result of the rapid developments in ballast water treatment operations, the question of whether ballast water treatment systems can be used as the main desalination system in the daily life of the crew on commercial vessels has been raised. This study introduces the current desalination systems on commercial vessels and their evaluation criteria. According to the literature and our professional industrial research, there are three most suitable alternatives such as “freshwater generator,” “reverse osmosis method,” and “attaching additional membrane filter to mechanical and ultraviolet (UV) ballast water treatment system.” Similarly, the evaluation criteria are determined as “installation cost of the system,” “operational cost of the system,” “risk of the system polluting the environment,” “risk of the system harming the human health,” “ease of repair and maintenance of the system,” “ease of use of the system,” and “ease of installing the system on the ship.” Due to the need for field expertise, we conducted several rounds of expert consultations. The novelty of this study is twofold. First, we improved the intuitionistic fuzzy TOPSIS (IF-TOPSIS) method by extending an expert prioritization technique. We also used an intuitionistic fuzzy scale for the expert weights. Second, as far as we know, this is the first study that employs an improved IF-TOPSIS method for desalination systems on commercial vessels. Moreover, we compared the proposed method and other methods to analyze the results. Results show that “freshwater generator” is more promising than “attaching additional membrane filter to mechanical and UV ballast water treatment system” that is prior to “reverse osmosis method.” This study helps the users and authorities understand the evaluation and select the desalination systems.

FAHP-Based Reliability Evaluation of Distributed IoT Devices in a Distribution Power Grid

Reliable operation of distributed internet of things (IoT) devices is essential for supporting two-way interaction between energy flow and information flow in a distribution power grid. Traditional reliability evaluation methods suffer from several challenges including complex evaluation indicator selection and inadaptability of fixed weights with actual reliability requirements. In this paper, we first establish a multilevel reliability evaluation indicator system, where the indicators are selected through joint consideration of comprehensiveness and effectiveness. Then, we propose a fuzzy analytic hierarchy process- (FAHP-) based reliability evaluation method, where a three-layer reliability evaluation architecture is established. Specifically, a 0.1-0.9 scaling method is adopted to establish the fuzzy judgment matrix and scale the important relationship among state-layer elements, which can be dynamically adjusted to generate the weights adapting with actual operation state. The scores of distributed IoT devices and corresponding reliability levels can be obtained through the weighted summation of the scores of each layer. Simulation results verify the effectiveness and accuracy of the proposed method through comparing with actual reliability value and two existing evaluation methods.

Analisis Perbandingan Implementasi Metode MADM dan Fuzzy MADM SAW Pada Sistem Pendukung Keputusan


 
 
 There are so many studies that use the Multi-Attribute Decision Making (MADM) method as a solution in Decision Support Systems. In addition, there are also many studies that use additional fuzzy which is implemented in the MADM method which is commonly referred to as Fuzzy MADM. For example, using Simple Additive Weighting (SAW), which one is closer to the best solution, whether to use MADM SAW or FMADM SAW, which one is better to use.
 Based on these problems, in this study analysis will be carried out regarding which method is closer to the best solution to be implemented in the case of Decision Support System between MADM and FMADM, in this case using the case of selecting the best graduates in the study program and the SAW method.
 Based on the results of the discussion in this study, it can be concluded that the implementation of MADM uses SAW, with 2 approaches, namely: Likert and fuzzy scales. The results obtained from the comparison of assessment ranges using the Likert and fuzzy scales obtained suitability of 100%. While the results of testing using RSD on Likert and fuzzy scales obtained the same results, namely 12.24%. The use of a Likert scale or fuzzy numbers has no effect, what affects the results is the range of the rating scale.
 
 

Difficulties experienced by managers in the coordination of teams working from home: an exploratory study considering the COVID-19 pandemic

PurposeThis research aims to analyse difficulties experienced by Brazilian managers in coordinating teams working from home during the coronavirus disease (2019) COVID-19 pandemic.Design/methodology/approachThe methodological strategy used was a survey with 39 managers who led teams working from home during the COVID-19 pandemic. Seven difficulties indicated by current literature were analysed using a fuzzy scale. First, a hierarchical cluster analysis (HCA) approach was used to group managers according to managers' similarities and capacity to infer the difficulties. Responses of each group identified were weighted considering the capacity to assess the theme. In the sequence, data were analysed via frequencies and the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) approach and difficulties were ordered.FindingsComparatively, the main difficulties evidenced are (1) to reconcile personal and professional life tasks in the same place; (2) to motivate collaborators in a period when social isolation affect employee's mental health and (3) to keep team members integrated and working within the activities scope in a virtual environment.Originality/valueThe findings present in this paper contribute to theory and practice. For theory, this article contributes to the knowledge on WFH and leadership, evidencing in a comparatively way the difficulties that are experienced by managers during the COVID-19 pandemic. Researchers in future studies can better analyse these difficulties. For practice, managers who conduct managers' teams remotely can use the information to analyse teams' practices and improve performance critically. This was an atypical moment of humanity, and different aspects need to be considered by managers compared with previous periods.

Evaluation of Control Priorities Based on a Matrix of Paired Comparisons

The article contains a description of the model and approach for determining the weights of controls (other objects) based on a matrix of pairwise comparisons. The initial data in the matrix of paired comparisons implicitly specify interval estimates for comparison of controls. Interval estimates can be constructed relatively easily using Harrington's fuzzy metric scale. A heuristic method for determining the priorities of controls is proposed, which seeks to obtain weights (priorities) of controls that deviate minimally from the boundary values of the weight intervals.The latter are easy to find using the system of relations, on the basis of which the matrix of pairwise comparisons of controls is built. To assess the statistical adequacy of the found control priorities, the determination coefficient is used, the value of which at the level of 80 % and above is considered practically acceptable for applications. The critical value of the coefficient of determination can be determined, for example, using the Fisher criterion. If the conditions of statistical adequacy are not met, the initial data in the matrix of paired comparisons should be revised. An example is provided to illustrate the method described in the article. The main advantages of the approach described in the article are the flexibility of the choice of interval estimates for pairwise comparison of controls, the relative simplicity of computational calculations, and the ability to control the calculation results using statistical criteria. The described method develops the authors' approach to the adoption of anti-crisis management by adapting management priorities to the conditions of the production system and its environment.

The methods of data processing according to the measurement/classification procedure for quality indicators of objects

The measurement/classification procedure of object properties, such as quality indicators, is used for determination of object quality category. According to measurement uncertainty, the fuzzy classification scale is constructed. In accordance with this scale, fuzzy classification results are obtained. The use of fuzzy averaging for multiple measurements of individual quality indicators are proposed. The fuzzy logic operators that can be used in the construction of group quality indicators are considered and recommendations for their application are given. As an example of application of the proposed method, the definition of water quality categories on its biochemical properties is used.

AN OBJECTIVE FUZZY CLASSIFIER ALGORITHM APPROACH FOR WATER QUALITY RECOGNITION

Water is the energy of life. Its usage and want, far out stretch any earth material (minerals, rocks, soil and water). In most cases the quantity of water obtains from its different sources are not quality enough for human usage due to the presence of contaminants. Several research works has been proposed on water quality recognition but none on the area of Artificial Intelligence (AI). This research paper adopts and proposes a fuzzy classifier algorithm approach for water quality recognition utilizing the decision variables pertaining to water, thereby enhancing or extending the traditional (conventional) method. The simulation of the algorithm was handled utilizing Matric Laboratory (MatLab). The result obtained based on the fuzzy scale was subdivided into three (might be pure water?, ?pure water? and ?not pure water?). The proposed expert system eliminates uncertainties and imprecision associated with the recognition of water quality

Data Processing by Fuzzy Methods in Social Sciences Researches. Example in Hospitality Industry

Likert-type scales are a common technique used in social science. Plus, the Likert scale is among the most frequently used psychometric tools in social sciences and educational research. Despite its frequently used, the Likert scale raises up many questions mark. We can say that the use of the Likert scale in its classical form is too rigid and loses valuable information. Li (2013, p. 1613) calls on previous studies that "have claimed that fuzzy scales are more accurate than traditional scales due to the continuous nature of fuzzy sets". The aim of this research is to reduce the inaccuracy caused by the use of the Likert scale, by proposing a method of more appropriate processing of data collected in this way. As shown in this paper, fuzzy methods can be a good alternative. The research methodology consists of using the usual technique on the set of fuzzy numbers by considering the input data as linguistic variables, subsequently identified by triangular fuzzy numbers. The obtained scale is more elastic with respect to the input data, therefore it better captures the reality. The newly proposed method is applied in the concrete example of the competitors in the hotel field. The Importance-Performance Competitor Analysis is utilized. A weakness of the method is due to the use in its application of data collection with the Likert scale. The results conclude on the situation of the competitors regarding each attribute considered as in the crisp version of the method, but the identification and processing of data correspond better to the aspects of subjectivity and uncertainty specific to human thinking. A novelty is also the obtaining of a hierarchy within each category of attributes from the quadrants proposed by the Important-Performance Analysis in relation to the competition.

An Integrated Fuzzy Analytic Hierarchy Process (AHP) Model for Studying Significant Factors Associated with Frequent Lane Changing.

Frequent lane changes cause serious traffic safety concerns, which involve fatalities and serious injuries. This phenomenon is affected by several significant factors related to road safety. The detection and classification of significant factors affecting lane changing could help reduce frequent lane changing risk. The principal objective of this research is to estimate and prioritize the nominated crucial criteria and sub-criteria based on participants’ answers on a designated questionnaire survey. In doing so, this paper constructs a hierarchical lane-change model based on the concept of the analytic hierarchy process (AHP) with two levels of the most concerning attributes. Accordingly, the fuzzy analytic hierarchy process (FAHP) procedure was applied utilizing fuzzy scale to evaluate precisely the most influential factors affecting lane changing, which will decrease uncertainty in the evaluation process. Based on the final measured weights for level 1, FAHP model estimation results revealed that the most influential variable affecting lane-changing is ‘traffic characteristics’. In contrast, compared to other specified factors, ‘light conditions’ was found to be the least critical factor related to driver lane-change maneuvers. For level 2, the FAHP model results showed ‘traffic volume’ as the most critical factor influencing the lane changes operations, followed by ‘speed’. The objectivity of the model was supported by sensitivity analyses that examined a range for weights’ values and those corresponding to alternative values. Based on the evaluated results, stakeholders can determine strategic policy by considering and placing more emphasis on the highlighted risk factors associated with lane changing to improve road safety. In conclusion, the finding provides the usefulness of the fuzzy analytic hierarchy process to review lane-changing risks for road safety.

A FUZZY SCALE APPROACH TO THE THOR ALGORITHM

The use of the Multicriteria Decision Support Hybrid Algorithm for Decision Making Processes with Discrete Alternatives, acronym THOR, requires from the decision maker, during the judgment insertion stage, a significant amount of information that needs to be valued, which may cause the decision maker great cognitive fatigue. Therefore, this article aims to reformulate the THOR algorithm, in the judgment insertion stage, based on the inclusion of a fuzzy measurement scale, allowing the decision maker to express only a single value judgment. This reformulation follows the three steps of a fuzzy system: fuzzification, fuzzy inference and defuzzification. In addition, a comparative analysis is performed between the THOR algorithm and its new version based on the construction of the fuzzy scale. It should be noted that its reformulation does not compromise the methodological efficiency of the THOR algorithm, it only reduces the complexity of decision making.

A novel risk analysis approach for occupational safety using Bayesian Network and interval type-2 fuzzy sets: the case of underground mining

Occupational safety problems are no longer acceptable for any industrial environment. Lack of comprehensive and reliable evaluations for occupational safety causes many undesired events and harm to employees during the industrial process. In this study, it is aimed to develop an applicable risk analysis methodology for evaluating the undesired occupational events that occurred in the multi-process system where no historical accident records. The difficulty in obtaining and analyzing the data required for the determination of the occupational safety risks especially in the manually executed processes has been overcome with the Bayesian Network and interval type-2 fuzzy sets by using the expert judgments. While BN enables to development of a comprehensive reasoning approach about the occurrence of the events, interval type-2 fuzzy sets better represent the ambiguity in the judgments by covering the uncertainty in a wider mathematical range with less computational effort according to other fuzzy sets. During multi-processes in industrial activity, various occupational undesired events may occur, including rare events with very serious consequences or frequent events with very low severity consequences. To able to consider all kinds of events occurring in an industrial environment from a holistic risk perspective, a novel fuzzy scale for specifying the probability and consequence of the events are proposed by the interval type-2 fuzzy numbers. Therefore, all undesired events regardless the probability and consequence which may occur during the multi-processes in a system and the main root causes of these events can be observed within the proposed methodology. A case study is used to emphasize the effect of the proposed methodology for risk analysis of occupational safety in underground mining. The results have indicated that occupational safety education is the most contributing factor to occurring the undesired occupational events in underground mining. We believe that this study could help evaluate the safety risk of the multi-process systems comprehensively and holistically and proposing strategic planning for mitigating the occupational safety risks.

Analysis of the agility of the automotive industry supply chain in times of COVID-19: a case study

In the early stages of the corona virus pandemic, business environment was changing rapidly. The Moroccan automotive industry was one of the export sectors most affected negatively by the corona crisis; it collapsed during the three months of confinement and the pandemic has created immense uncertainties in demand and disrupted global supply chains. Indeed, to save the automotive industry, Morocco relies on its competitiveness and challenges current supply models for supply chain agility in order to better prepare for future disruptions. Achieving a competitive edge requires aligning company with suppliers and customers as well as working together to achieve agility, organizationally, strategically and individually. However, agile supply chains are the most powerful competitive vehicles of the manufacturing companies. To help automakers deal with the many challenges associated with the pandemic, let’s present this research on the key enablers that will need to be monitored as the situation evolves. Thus, our article presents an original approach which, by linking the competitive priorities, agile supply chain attributes and enablers, aims at evaluates and enhances supply chain agility of a Moroccan automotive factory. Let’s adopt fuzzy quality function deployment (FQFD) approach and, in particular, the two houses of quality (HOQ) with a fuzzy scale in order to identify the most appropriate enablers to be implemented by the factory. This evaluation demonstrates that there are three enablers needing maximum attention: process compliance, logistics and distribution capabilities and supportive information technology. Then, the supply chain agility improvement should be based on these enablers

직관 퍼지 와이블 분포에서 알파 컷 셋을 이용한 시스템 신뢰성 분석

Purpose This study is to analyze system reliability using fuzzy Weibull lifetime distribution in which scale parameters are assumed to be Intuitionistic Fuzzy Set (IFS) with α-cut set due to uncertainties and inaccuracy of data. Methods The IFS is utilized to present the information of membership function and non-membership function with the three intervals that include belief, disbelief and unbelief functions. The paper discusses the intuitionistic fuzzy Weibull system reliability models to assess the membership function and non-membership function by considering the different types of component intuitionistic fuzzy scale parameter. Due to the existence of different types of uncertainties, the three types of component TIFS (Triangular IFS) and TrIFS (Trapezoidal IFS) with α-cut set were presented for computing intuitionistic fuzzy system reliability in both series structure and parallel structure. Results The validity of proposed model is demonstrated by analyzing intuitionistic fuzzy Weibull system reliabilities with α-cut set using different types of intuitionistic fuzzy scale parameter. A numerical example is indicated to discuss the usefulness and practicality of the proposed model. Conclusions When conducting a group decision making for evaluating the intuitionistic fuzzy Weibull system reliability, α-cut set models proposed in this paper can be used to reflect various experts’ judgments on agreement, disagreement and undecidedness when evaluating system reliability.

Fuzzy multiple objective fractional optimization in rough approximation and its aptness to the fixed-charge transportation problem

This article presents a multiple objective fractional fixed-charge transportation problem (MFFTP) in a rough decision-making framework. A transformation procedure is modified to convert non-linear multi-objective transportation problem to its linear version. The parameters of the designed model are considered to be fuzzy. We employ separate kinds of fuzzy scale, i.e., possibility, credibility and necessity measures, to deal with the fuzzy parameters. Using the fuzzy chance-constrained rough approximation (FCRA) technique, we extract the more preferable optimal solution from our suggested MFFTP. The initial result is compared with that of the robust ranking (RR) technique. We also use the theory of rough sets for expanding as well as dividing the feasible domain of the MFFTP to accommodate more information by considering two approximations. Employing these approximations, we introduce two variants, namely, the lower approximation (LA) and the upper approximation (UA), of the suggested MFFTP. Finally, by using these models, we provide the optimal solutions for our proposedproblem. We also associate our MFFTP with a real-world example to showcase its applicability as well as performance. Our core concept of this article is that it tackles an MFFTP using two separate kinds of uncertainty and expands its feasible domain for optimal solutions. Optimal solutions of the designed model (obtained from FCRA technique) belong to two separate regions, namely, “surely region” and “possible region”. The optimal solution which belongs to the “surely region” is better (as these are minimum values) than the one in the “possible region” and other cases. An interpretation of our approach along with offers about the intended future research work are provided at last.

Mapping Generation Y Tourists’ E-Loyalty: A Sustainable Framework through Hierarchical Structure and Fuzzy Set Theory

Generation Y (Gen Y) travel spending is set to soar and has enormous implications for hospitality firms’ economic sustainability. However, previous studies have failed to examine the hierarchical interrelationship between e-loyalty attributes in the presence of a hierarchical structure and linguistic preferences. Consequently, the purpose of this paper is to identify a list of e-loyalty attributes and to examine each attribute’s importance to Gen Y consumers’ e-loyalty intentions in the context of tourism. Drawing on an ad hoc survey of 230 graduate students in Taiwan, the study employs exploratory factor analysis to analyze the method’s validity and reliability. Furthermore, 30 Gen Y consumers are invited to evaluate the identified measures using fuzzy linguistic scales. The fuzzy set theory is then employed to translate the qualitative responses into crisp values. The decision-making trial evaluation laboratory is used to understand the interrelationships between the e-loyalty attributes. The empirical findings reveal that trust, utilitarian features, and hedonic features all play essential roles in Gen Y tourists’ e-loyalty. In addition, perceived enjoyment, website competency, emotional connection, candid and authentic site information, and delightful experiences are crucial factors in the formation of customer e-loyalty. Both theoretical and managerial implications are discussed.

Fuzzy Multi Criterion Decision Making Method to Analyze Performance of Banking Sector

Performance evaluation of any financial institution is extremely important to look after the health and prospect of the institution. In many research of performance evaluation analysis of banks, several ratio parameters are used mostly in statistical analysis. Designing effective and comprehensive model for evaluation process of financial matters in banking sector is complex due to multiple criteria and parameters, mostly uncertain in nature. This paper presents a comprehensive process considering several financial criteria of several alternatives on the basis of several expert’s (decision maker’s) opinion and subjective judgment. Intensity of importance is represented in fuzzy scale. We used fuzzy AHP-preference programming (FPP) to obtain priority weights associated with each criteria and compromise ranking method (VIKOR) considering Market Capital, Net Sales, Net Profit, Total Assets, and Other Income in ranking alternatives. A case study involving ten active Indian Public Sector Unit (PSU) banking industries is undertaken to illustrative the feasibility of the suggested approach. A sensitivity analysis is also carried out for checking the method reliability.

Item Response Theory Models for the Fuzzy TOPSIS in the Analysis of Survey Data

The fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is an attractive tool for measuring complex phenomena based on uncertain data. The original version of the method assumes that the object assessments in terms of the adopted criteria are expressed as triangular fuzzy numbers. One of the crucial stages of the fuzzy TOPSIS is selecting the fuzzy conversion scale, which is used to evaluate objects in terms of the adopted criteria. The choice of a fuzzy conversion scale may influence the results of the fuzzy TOPSIS. There is no uniform approach in constructing and selecting the fuzzy conversion scale for the fuzzy TOPSIS. The choice is subjective and made by researchers. Therefore, the aim of the article is to present a new, objective approach to the construction of fuzzy conversion scales based on Item Response Theory (IRT) models. The following models were used in the construction of fuzzy conversion scales: Polychoric Correlation Model (PM), Polytomous Rasch Model (PRM), Rating Scale Model (RSM), Partial Credit Model (PCM), Generalized Partial Credit Model (GPCM), Graded Response Model (GRM), Nominal Response Model (NRM). The usefulness of the proposed approach is presented on the example of the analysis of a survey’s results on measuring the quality of professional life of inhabitants of selected communes in Poland. The obtained results indicate that the choice of the fuzzy conversion scale has a large impact on the closeness coefficient values. A large difference was also observed in the spreads of triangular fuzzy numbers between scales based on IRT models and those used in the literature on the subject. The use of the fuzzy TOPSIS with fuzzy conversion scales built based on PRM, RSM, PCM, GPCM, and GRM models gives results with a greater range of variability than in the case of fuzzy conversion scales used in empirical research.

A Weighted Combination Forecasting Model for Power Load Based on Forecasting Model Selection and Fuzzy Scale Joint Evaluation

To solve the medium and long term power load forecasting problem, the combination forecasting method is further expanded and a weighted combination forecasting model for power load is put forward. This model is divided into two stages which are forecasting model selection and weighted combination forecasting. Based on Markov chain conversion and cloud model, the forecasting model selection is implanted and several outstanding models are selected for the combination forecasting. For the weighted combination forecasting, a fuzzy scale joint evaluation method is proposed to determine the weight of selected forecasting model. The percentage error and mean absolute percentage error of weighted combination forecasting result of the power consumption in a certain area of China are 0.7439% and 0.3198%, respectively, while the maximum values of these two indexes of single forecasting models are 5.2278% and 1.9497%. It shows that the forecasting indexes of proposed model are improved significantly compared with the single forecasting models.

Evaluation of the Influencing Factors of Using Underground Space of Abandoned Coal Mines to Store Hydrogen Based on the Improved ANP Method

Storage is currently a major obstacle to the promotion of hydrogen energy. Hydrogen storage in abandoned coal mines can achieve the effective use of underground space while meeting the growing demand for energy storage facilities, which can bring economic and environmental benefits. However, research in this area has been limited to the conceptual discussion stage, without establishing a scientific evaluation method for the potential of modifying and utilizing abandoned coal mine space. In this study, based on the analytic network process (ANP), the Apriori algorithm is introduced to mine the association rules for various influencing factors. First, the Apriori algorithm is applied to mine association rules between indicators, eliminate unnecessary influence relationships, simplify the network structure model, and optimize the ANP weight calculation results; second, the solution method of judgment matrix is improved with triangular fuzzy numbers, and the index weight is solved by fuzzy nine marks instead of the method of nine scale, which is convenient for experts to give the fuzzy scale while better reflecting the opinions of experts. Finally, the ANP algorithm is applied to rank the weights of the obtained influencing factors, discuss the main factors with higher weights, and analyze the feasibility of converting candidate coal mines into hydrogen storage facilities using the derived evaluation method in the case study. The evaluation methods and conclusions presented in this study provide analytical tools and a decision basis for analyzing the feasibility of converting underground space of abandoned coal mines into hydrogen storage facilities and assessing the economic indicators.

Selection of Suitable Lubricant for Sliding Contact Bearing and the Effect of Different Lubricants on Bearing Performance: A Review and Recommendations

The word bearing implies to an element of the machine which allows one moving or vibrating part to support other rubbing surfaces by which the load can transmit. Depending upon in nature and application of load, an extensive variety of different bearing is available. They can generally be categorized into two kinds of bearing such as rolling element bearing and a sliding bearing. Lubrication is required in the middle of rubbing surfaces, which enacts as a medium between the moving surfaces to diminish friction and to take away heat for survival during the transmission of the load. In this paper, a literature review has been made on the influence of different lubricants on the performance of various bearing. The selection of an appropriate lubricant is a very critical decision to take for the efficient performance of a bearing because each lubricant has its own merits and demerits on various kinds of bearing. In the later portion of this paper, a selection process of right lubricant in sliding contact bearing is analyzed mathematically. This critical decision is being made by using PROMETHEE method (broadly Preference Ranking Organization Method for Enrichment Evaluations) hybridized by Entropy Weight Measurement method and Fuzzy scale. As per the ranking of Entropy-PROMETHEE method, the best suited lubricant for sliding contact bearing is SAE20W40.