Trapezoidal Spherical Fuzzy Numbers and its Application to Fuzzy Risk Analysis

Spherical fuzzy sets are a broader type of fuzzy sets that have the ability to handle various scenarios using their membership, non-membership, and neutral membership grades. These sets require that the total of the squares of these grades be no greater than one. This condition extends the possible values for the three grades and enables decision makers to have a wider range of options when assessing a situation. In solving real life problems, it is necessary to describe a real number as a spherical fuzzy set to incorporate the fuzziness, thus, the need to use trapezoidal spherical fuzzy numbers (TSFN).  In this paper, the membership functions of the TSFN, their arithmetic operations and their properties are discussed. Also, a ranking function is proposed to order the TSFNs. All these are used to solve a fuzzy risk analysis problem whose parameters are presented as TSFNs

(R1500) Type-I Generalized Spherical Interval Valued Fuzzy Soft Sets in Medical Diagnosis for Decision Making

In the present communication, we introduce the concept of Type-I generalized spherical interval valued fuzzy soft set and define some operations. It is a generalization of the interval valued fuzzy soft set and the spherical fuzzy soft set. The spherical interval valued fuzzy soft set theory satisfies the condition that the sum of its degrees of positive, neutral, and negative membership does not exceed unity and that these parameters are assigned independently. We also propose an algorithm to solve the decision making problem based on a Type-I generalized soft set model. We introduce a similarity measure based on the Type-I generalized soft set model for two Type-I generalized spherical interval valued fuzzy soft sets and discuss its application in a medical diagnosis problem. Illustrative examples are mentioned to show that they can be successfully used to solve problems with uncertainties

Analysis of development and effects of electronic trade in Serbia based on SF-TOPSIS and TOPSIS methods

The issues of measuring and analysing the development dynamics and effects of electronic trade are currently topical, significant and complex in any country, including Serbia. In the observed period from 2017 to 2021, according to the obtained empirical results based on the SF TOPSIS method, the largest number of trading companies introducing e-business (IT technology) and e-trading appeared in Serbia in 2017. According to the obtained empirical results based on the classical TOPSIS method, the largest number of trading companies introducing e-business (IT technology) and e-trading was recorded in Serbia in 2019. The following is the ranking according to the SF-TOPSIS method: 2021, 2018, 2019 and 2020. The ranking according to the TOPSIS method is as follows: 2020, 2021, 2018 and 2017. The digitalisation factors of overall business operation of trade industry in Serbia are the global trend and requirements, degree of development of contemporary IT technology and the possibility of application in all the segments of trading operations, the economic climate, financial opportunities, entry of international retail chains, development of multichannel sale-classic and e-retail facilities, around-the clock business operations without time and geographical barriers etc. Considering the positive effects, significantly more should be invested in new information and communication technology in the future

The Interval-Valued Spherical Fuzzy Based Methodology and its Application to Electric Car Selection

Imagining, thinking, producing, developing and changing what you produce are among the main traits that make human beings human. Human beings question their raison d’être, their life, the quality of their lives; in other words, they ask why and how. All these inquiries result in the production of information, a flow of the information produced, and sometimes a product. Today, in a world where production takes place at an unprecedented pace, one needs to possess the technology to keep up with developments. This is a dynamic capability and must be continuously developed to make it endure. Electric vehicles, a gift of technological developments of the world of today, are a combination of imagination, a needs assessment, and sustainable innovations. This study addressed the problem of electric car selection and included a case study involving six criteria and ten alternatives. The proposed decision model has integrated AHP and ELECTRE methods with interval-valued spherical fuzzy sets. The novelty of this study stems from evaluating the performance of electric cars using IVSF-AHP-ELECTRE and selecting accordingly for the first time. In this study, the level of importance of battery capacity, autonomous driving, charging network, price, efficiency and performance criteria were determined. A ranking was then made for the electric car alternatives based on these criteria

Elevating decision management in sustainable energy planning through spherical fuzzy aggregation operators

This article introduces a novel paradigm for enhancing the administration of decisions regarding sustainable energy planning. This is achieved by deploying novel spherical fuzzy aggregation operators that have been meticulously tailored to address the inherent complexities of uncertainty and imprecision prevalent in energy planning datasets. These operators vastly increase the precision and efficacy of decision-making processes, thereby transforming the entire sustainable energy landscape. This study focuses predominantly on the complex domain of multi-attribute decision-making (MADM), in which the interplay of parameters is characterized by a discernible hierarchy of importance. This method generates aggregation operators based on the assignment of non-negative real values to clearly defined priority echelons, a framework known as priority degrees. This effort results in the development of two notable prioritized operators: the “spherical fuzzy prioritized averaging operator with priority degrees” and the “spherical fuzzy prioritized geometric operator with priority degrees”. The efficacy of these conceptual frameworks is vividly demonstrated through the application of extensive case studies, in which observable results clearly demonstrate their superiority over conventional methodologies. The empirical findings unequivocally demonstrate the superiority of the proposed operators, resonating with substantial performance and efficiency improvements. This study not only adds a seminal dimension to the field of sustainable energy management but also reveals a revolutionary application of spherical fuzzy aggregation operators at the forefront of effective decision-making paradigms. The seamless fusion of theoretical innovation and practical utility outlines a path forward, with transformative prospects and far-reaching implications for the sustainable energy landscape

Comprehensive evaluation of the effectiveness of endemic disease prevention and control in Jiangsu Province, China, 2013–2022

As a strong economic and populous province in China, Jiangsu is home to four endemic diseases. Despite efforts in the past decade, the prevention and control of these four endemic diseases are not uniform because of the different etiological chains and influencing factors of these diseases. Among the evaluation methodologies for endemic disease control, only one method is currently available for each disease. In this study, we selected 14 indicators to comprehensively evaluate the effectiveness of endemic disease control in Jiangsu between 2013 and 2022. We improved the method for calculating the weights of the indicators and established a fuzzy comprehensive evaluation model based on the weighted Technique for Order Preference by Similarity to an Ideal Solution model and a weighted grey relational analysis model. The results of the comprehensive evaluation showed that the progress of endemic disease control in Jiangsu was not always in line with our expectations of improvement, with the top five years of better control occurring in 2015, 2013, 2021, 2022, and 2014. The results of the sensitivity analysis confirm the reliability and accuracy of these findings. We discovered that measures such as the reform of the salt industry, use of thyroid ultrasound, and new water supply projects for residents in Jiangsu affected the progress of endemic disease prevention and control. The tracking of endemic disease status should consider the potential effects of changes in policies implemented in other industries on endemic disease prevention and control. Additionally, the results of this study provide a theoretical basis for enhancing prevention and control practices in other regions of China

Interval- valued fermatean neutrosophic graphs

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