Comparison of Single Transmit Queuing System Including Proportions of Execution Using Fuzzy Queuing Model and Intuitionistic Fuzzy Queuing Model with Two Classes

Abstract

This research provides a two-class single transmit queuing model. We also calculate the model's execution proportions under a vague environment. The main purpose of this inquiry is to compare the results of a single transmit queuing model based on fuzzy queuing theory and intuitionistic fuzzy queuing theory. Triangular fuzzy numbers and triangular intuitionistic fuzzy numbers are used to describe the entry (arrival) and administration (service) rates. The fuzzy queuing theory model's evaluation metrics are supplied as a range of values, but the intuitionistic fuzzy queuing theory model offers a wide range of values. An analysis is offered to discover quality measures utilizing a proposed methodology in which the fuzzy values are retained as is without being altered into crisp values, hence we can use the proposed method to draw scientific conclusions in an uncertain environment. Two numerical problems are solved to demonstrate the sustainability of the suggested method. Subsequently, prototype components were exposed to sensitivity analyses. Sensitivity testing is used to find discrepancies between the two groups when calculating their execution proportions. We employed the triangular fuzzy number in an intuitionistic fuzzy environment in this study, accounting for the degree of comfort and refusal so that the sum of both values is always less than 1. For this type of fuzzy integer, we gave various non-normal arithmetic procedures. The proposed formulations are simple and direct, having been devised using classical algebraic mathematics. This strategy is simple and straightforward to use in actual situations. The nearest interval number is then used to round a TIFN. The key benefit of this approach is that using a multi-section algorithm, we can quickly solve a bound unbridled optimization problem with coefficients as TIFN. The present methodologies and strategies are intended to be applicable to a variety of contemporary decision-making challenges in areas of economic share, finance, administration, and ecology, which are the focus of our future study.

Rules Determination Based on Time-Series Data to Classify Unsupervised Cases Based on Fuzzy Expert System

“…[11] is also conducting research in the health sector that uses IFS for brain image segmentation. Whereas [12] conducted a study demonstrating the queuing model using the fuzzy technique in two classes. The findings indicate that the intuitionistic fuzzy approach is more adaptable.…”

“…However, most of the studies only focus on the membership function (MF). It is also important to consider the non-membership function, which has the ability to significantly reduce the degree of hesitation, as revealed by [12]. We aim to compare the effectiveness of both conventional fuzzy systems and intuitionistic fuzzy systems for this reason.…”