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首页> 外文期刊>Pesquisa Operacional >DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM
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DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM

机译：交通系统离散事件仿真模型中的人工神经网络决策

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摘要

This work aims to demonstrate the use of a mechanism to be applied in the development of the discrete-event simulation models that perform decision operations through the implementation of an artificial neural network. Actions that involve complex operations performed by a human agent in a process, for example, are often modeled in simplified form with the usual mechanisms of simulation software. Therefore, it was chosen a traffic system controlled by a traffic officer with a flow of vehicles and pedestrians to demonstrate the proposed solution. From a module built in simulation software itself, it was possible to connect the algorithm for intelligent decision to the simulation model. The results showed that the model elaborated responded as expected when it was submitted to actions, which required different decisions to maintain the operation of the system with changes in the flow of people and vehicles.
机译：这项工作的目的是演示一种机制，该机制可用于开发离散事件仿真模型，该模型通过实现人工神经网络来执行决策操作。例如，涉及人员在流程中执行的复杂操作的动作通常以简化形式通过模拟软件的常规机制进行建模。因此，选择了一个由交通官员控制的交通系统，其中有车辆和行人通行，以演示所提出的解决方案。通过内置于仿真软件本身的模块，可以将用于智能决策的算法连接到仿真模型。结果表明，精心设计的模型在付诸行动时能按预期做出响应，这需要不同的决策来随着人员和车辆流量的变化保持系统的运行。

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