ANFIS Computing for M/M/\(\infty\) Queue with Two Types of Service Interruption and Balking

IF 0.8 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Proceedings of the National Academy of Sciences, India Section A: Physical Sciences Pub Date : 2023-04-05 DOI:10.1007/s40010-023-00821-3
Neetu Singh, Madhu Jain, Sibasish Dhibar
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Abstract

In this investigation, we study the M/M/\(\infty\) queueing system with server breakdown and two different types of customers called loss and delay customers. The system is subject to random service interruptions due to server breakdown; the broken-down server will be recovered after repair provided by a repairman according to exponential distribution. Due to server breakdown, there may be either fully or partially interruptions in service, i.e., during breakdown each server may stop providing service or provide service with compromised efficiency. The customers’ balking behavior is incorporated during the service interruptions. The stochastic decomposition property for the system size has also established. The sensitivity analysis has performed by taking numerical examples. Adaptive neuro-fuzzy inference system (ANFIS) technique is implemented to develop ANFIS controller so as to evaluate the simulation results by including the realistic feature of fuzzy descriptors which may be noticed at several queueing scenarios.

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具有两种服务中断和逡巡的 M/M/(\infty\)队列的 ANFIS 计算
在本研究中,我们研究了具有服务器故障和两种不同类型客户(称为损失客户和延迟客户)的 M/M/(infty/)队列系统。该系统会因服务器故障而发生随机服务中断;故障服务器将在维修人员根据指数分布提供维修后恢复。由于服务器故障,服务可能会完全中断或部分中断,即在故障期间,每台服务器可能会停止提供服务或提供服务的效率受到影响。在服务中断期间,客户的逡巡行为也会被考虑在内。此外,还确定了系统规模的随机分解属性。通过数字示例进行了敏感性分析。采用自适应神经模糊推理系统(ANFIS)技术来开发 ANFIS 控制器,从而评估模拟结果,其中包括在多个排队场景中可能注意到的模糊描述符的现实特征。
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来源期刊
CiteScore
2.60
自引率
0.00%
发文量
37
审稿时长
>12 weeks
期刊介绍: To promote research in all the branches of Science & Technology; and disseminate the knowledge and advancements in Science & Technology
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