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INTEGRATION OF ANN MLP AND COMPUTER SIMULATION FOR INTELLIGENT DESIGN OF QUEUING SYSTEMS

机译:广进系统智能设计的ANN MLP与计算机仿真的集成

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This paper describes a framework for design and development of intelligent simulation environment for queuing system. The intelligent simulation environment utilizes Artificial Neural Network (ANN) to simulate and optimize a complex queuing system. The integrated simulation ANN model is a computer program capable of improving its performance by referring to production constraints, system's limitations and desired targets. It is a goal oriented, flexible and integrated approach and produces the optimum solution by utilizing Multi Layer Perceptron (MLP). The properties and modules of the prescribed intelligent simulation ANN are: 1) parametric modeling, 2) flexibility module, 3) integrated modeling, 4) knowledgebase module, 5) integrated database and 6) learning module. The integrated simulation ANN is applied to 30 distinct G/G/K queuing systems. Furthermore, its superiority over conventional simulation approach is shown in two dimensions which are running time and number of required iterations.
机译:本文介绍了对排队系统智能仿真环境的设计和开发的框架。智能仿真环境利用人工神经网络(ANN)来模拟和优化复杂的排队系统。集成仿真ANN模型是一种计算机程序,可以通过参考生产约束,系统的限制和所需目标来提高其性能。它是一种面向目标,灵活和集成的方法,通过利用多层Perceptron(MLP)来产生最佳解决方案。规定智能仿真ANN的属性和模块是:1)参数化建模,2)灵活模块,3)集成建模,4)知识库模块,5)集成数据库和6)学习模块。集成的仿真ANN应用于30个不同的G / G / K排队系统。此外,其优于传统模拟方法的优势在于运行时间和所需迭代的数量的两个维度。

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