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A new optimum statistical estimation of the traffic intensity parameter for the M/M/1/K queuing model based on fuzzy and non-fuzzy criteria | ||
| Journal of Data Science and Modeling | ||
| دوره 2، شماره 1 - شماره پیاپی 3، اسفند 2023، صفحه 163-184 اصل مقاله (316.48 K) | ||
| نوع مقاله: original | ||
| شناسه دیجیتال (DOI): 10.22054/jdsm.2024.79643.1048 | ||
| نویسنده | ||
| Iman Makhdoom* | ||
| Payame Noor University | ||
| چکیده | ||
| This article focuses on the M/M/ 1 /K queuing model. In this model, the inter-arrival times of customers to the system are random variables with an exponential distribution parameterized by λ , and the service times of customers are random variables with an exponential distribution parameterized by µ . We aim to estimate the traffic intensity parameter of this model using Bayesian, E-Bayesian, and hierarchical Bayesian methods. These methods utilize the entropy loss function and an appropriate prior distribution for the independent parameters λ and µ . Additionally, we employ the shrinkage-based maximum likelihood estimation method to obtain the parameter estimates. To determine the desired traffic intensity parameter estimate, we introduce a decision criterion based on a cost function, and a fuzzy criterion called the Average Customer Satisfaction Index (ACSI). The goal is to select the estimation with a higher ACSI index. To facilitate understanding, we compare this estimation using the Monte Carlo simulation method and two numerical examples based on the ACSI index. | ||
| کلیدواژهها | ||
| M/M/1/K queuing model؛ traffic intensity parameter؛ cost function؛ ACSI | ||
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آمار تعداد مشاهده مقاله: 193 تعداد دریافت فایل اصل مقاله: 308 |
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