2017
DOI: 10.9790/9622-070503136139
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The Analysis of Performance Measures of Generalized Trapezoidal Fuzzy Queuing Model with an Unreliable Server

Abstract: The purpose of this research paper was to propose a method which can be utilized to determine the different types of performance measures on the basis of the crisp values for the fuzzy queuing model which has an unreliable server and where the rate of arrival, the rate of service, the rate of breakdown and the rate of repair are all expressed as the fuzzy numbers. In this case the inter arrival time, the time of service, the rates of breakdown and the rates of repair are all triangular functions and are also e… Show more

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Cited by 1 publication
(2 citation statements)
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“…In recent years, nanoparticles have attracted attention in terms of removing biological pollutants from wastewater. Because new technologies such as nanoparticles that decontaminate biological pollutants in wastewater without producing harmful by-products are a serious need globally [24]. Nanomaterials are structures with properties that make biological waste an attractive separation medium for wastewater treatment [25].…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…In recent years, nanoparticles have attracted attention in terms of removing biological pollutants from wastewater. Because new technologies such as nanoparticles that decontaminate biological pollutants in wastewater without producing harmful by-products are a serious need globally [24]. Nanomaterials are structures with properties that make biological waste an attractive separation medium for wastewater treatment [25].…”
Section: Resultsmentioning
confidence: 99%
“…LSTMs were specifically designed to address the vanishing gradient problem and enable the modeling of long-range dependencies in sequential data [22,23]. In this section, we will explore LSTMs comprehensively, covering their architecture, components, advantages over vanilla RNNs, real-world applications, variations, and case studies in natural language processing (NLP) and time series prediction [24,25].…”
Section: Long Short-term Memory Network (Lstms)mentioning
confidence: 99%