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Data regarding dynamic performance predictions of an aeroengine

机译:关于航空发动机的动态性能预测的数据

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The design of aeroengine real-time control systems needs the implementation of machine learning based techniques. The lack of in-flight aeroengine performance data is a limit for the researchers interested in the development of these prediction algorithms. Dynamic aeroengine models can be used to overcome this lack.This data article presents data regarding the performance of a turbojet that were predicted by the dynamic engine model that was built using the Gas turbine Simulation Program (GSP) software.The data were also used to implement an Artificial Neural Network (ANN) that predicts the in-flight aeroengine performance, such as the Exhaust Gas Temperature (EGT).The Nonlinear AutoRegressive with eXogenous inputs (NARX) neural network was used. The neural network predictions have been also given as dataset of the present article.The data presented here are related to the article entitled “MultiGene Genetic Programming - Artificial Neural Networks approach for dynamic performance prediction of an aeroengine” .
机译:航空发动机实时控制系统的设计需要基于机器学习的技术实现。缺乏航班航空发动机性能数据是对对这些预测算法的开发感兴趣的研究人员的限制。动态航空发动机模型可用于克服这种缺乏。这篇数据文章介绍了有关使用燃气轮机模拟程序(GSP)软件建造的动态发动机模型预测的Turbojet性能的数据。数据也用于实施一种人工神经网络(ANN),其预测飞行飞行空气发动机性能,例如排气温度(EGT)。使用外源输入(NARX)神经网络的非线性归类。作为本文的数据集,神经网络预测也被给出。这里呈现的数据与标题为“用于动态性能预测的多岛遗传编程 - 人工神经网络方法”的文章有关。

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