Applied Mathematics in Science and Engineering (Dec 2023)
Mathematical insights into interval solutions of fuzzy relation inequalities for effective Information resource sharing in business education
Abstract
To examine the connectivity of educational and business institution networks and assess their resource accessibility, we have employed min-max fuzzy relation systems. This piece aims to delve into the outcomes resulting from various factors within a three-compartmental financial system. The research undergoes the dynamical max-min fuzzy solutions, which are expressed in an interval format. These solutions take into consideration variables such as the price index, interest rate, investment demand, fluctuations, cost per investment derived from saved funds, and the elasticity of market demand within the commercial sector. These variables are essential for comprehending the dynamics of the three-compartment financial system. It is difficult to obtain the entire set of solutions for the max-min fuzzy relation system using only minimal solutions. Some of these systems can be solved using optimized fuzzy relation models for both maximal and minimal solutions. Therefore, by converting the business market's financial system into a max-min fuzzy relation inequality, the strategy presented in this article tries to get the broadest and changing solution fluctuating between minimal and maximal solutions. With this suggested strategy for solving the problem, the limiting upper and lower values within which the given quantities fluctuate are identified. By measuring the breadth of the resulting interval, the range of fluctuation may be identified, giving a thorough insight into the system's behaviour. Due to the potential instability of market agents and their respective influences, fluctuations may occur in the demand, supply, and prices of indices in the financial system. Consequently, presenting the financial system in the format of the widest fuzzy interval solution can provide easily accessible information to the general public by illustrating the max-min fuzzy relation system of financial dynamics, outlining the necessary steps, and including a numerical example.
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