Semi-Circular Fuzzy Variable And Its Properties

2021 ◽  
pp. 105-119
Author(s):  
Palash Dutta
Keyword(s):  
Author(s):  
Ekaterina Tereshko ◽  
Marina Romanovich ◽  
Irina Rudskaya

The construction industry is high-tech and is one of the key areas for the strategic development of regions in terms of their digitalization. The construction complex provides regions with infrastructure of various levels from design documentation to commissioning, as well as reconstruction and major repairs of buildings. The article adopts an isolated regional approach, which is due to the need to assess specific territories by the level of readiness for digitalization of the construction complex. The purpose of the research is to determine the level of readiness of Russian regions for the digitalization of the construction complex by forming a rating of regions according to the indicator “the level of readiness of the region for digitalization of the construction complex”. To build the rating, the fuzzy sets method was applied using a triangular membership function, which allows to describe the influence of various processes on the formation of digitalization processes in the construction complex of the region. When forming the rating, a scale of fuzzy variable values is set which allows one to classify regions by levels, namely very low, low, medium, high, and very high. The generated rating is illustrated according to the specified scale. Based on the rating, the leading regions and outsider regions are identified by the formed indicator. It was determined that Moscow and Saint Petersburg are highly prepared for the digitalization of their construction complexes, and 53 regions of Russia are potentially prepared. In the future, it will be possible to create a rating of Russian regions on the level of readiness for digitalization of the construction complex with a two-year lag. Then, using the DEA shell analysis method, a quantitative assessment will be carried out that allows you to form performance boundaries and, against the background of four years, adjust the data to identify the most realistic picture. Also, the rating methodology considered by the authors allows us to scale this research to the international level, which will allow us to assess the level of digital development of construction complexes in other countries. The proposed rating algorithm is suitable for other sectors and complexes of the economy. It is enough to determine the main aggregate indicator and select groups of factors.


Author(s):  
Pratibha Verma ◽  
Manoj Kumar

This work provides a new fuzzy variable fractional COVID-19 model and uses a variable fractional operator, namely, the fuzzy variable Atangana–Baleanu fractional derivatives in the Caputo sense. Next, we explore the proposed fuzzy variable fractional COVID-19 model using the fixed point theory approach and determine the solution’s existence and uniqueness conditions. We choose an appropriate mapping and with the help of the upper/lower solutions method. We prove the existence of a positive solution for the proposed fuzzy variable fractional COVID-19 model and also obtain the result on the existence of a unique positive solution. Moreover, we discuss the generalized Hyers–Ulam stability and generalized Hyers–Ulam–Rassias stability. Further, we investigate the results on maximum and minimum solutions for the fuzzy variable fractional COVID-19 model.


2015 ◽  
Vol 15 (2) ◽  
pp. 6480-6490
Author(s):  
Mohd Muqeem ◽  
Dr. Md. Rizwan Beg

The importance of the prioritization in commercial software development has been analyzed by many researchers. The gathered requirements are required to be put into an order of some priority. In other words we can say that there is a need to prioritize the requirements. It is evident that most of the approaches and techniques proposed in recent research to prioritize the requirements have not been widely adopted. These approaches are too complex, time consuming, or inconsistent and difficult to implement In this paper we propose a fuzzy based approach for requirement prioritization in which  requirement are prioritized in early phase of requirement engineering as post elicitation step. This category of prioritization is known as early requirement prioritization. The proposed fuzzy based approach considers the nature of requirements by modeling their attributes as fuzzy variables. As such, these variables are integrated into a fuzzy based inference system in which the requirements represented as input attributes and ranked via the expected value operator of a fuzzy variable.


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