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THE APPLICATION OF RBFN NEURAL NET IN AN ENERGY LOSS DETECTION SYSTEM FOR A 125MW UNIT

机译:RBFN神经网络在125MW单位的能量损耗检测系统中的应用

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In order to solve the problem of failure data, a simulation method based on radial basis function networks (RBFN) is used in an energy loss detection system. This paper introduces the characteristics of RBFN net and how to determine it's key parameters. And then it expounds its learning process, the selection of the samples and the error analysis of the simulation results. Its application has proved that the method is not only accurate enough but also very feasible for on-line and real-time detection.
机译:为了解决故障数据的问题,在能量损耗检测系统中使用基于径向基函数网络(RBFN)的仿真方法。本文介绍了RBFN网的特点以及如何确定其关键参数。然后阐述了其学习过程,选择样本和仿真结果的误差分析。其应用证明了该方法不仅足够准确,而且对于在线和实时检测也是非常可行的。

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