用神经网络确定跳跃监测参数

S. Klevtsov
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引用次数: 0

摘要

设计了技术对象参数危险变化预警模型和算法。该算法基于所构造的图,并实时运行。表征参数图形式的时间序列点局部阵列。图上每个点的当前参数值和下面的参数值形成。首先确定时间窗口。沿着时间序列移动的数组截断时间窗口。传感器数据在形成时间序列的过程中被使用。使用改进的神经网络来确定参数的危险变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determination jump monitored parameter using a neural network
Model and algorithm of warning about the dangerous change in the parameter of the technical object designed. The algorithm is based on the diagrams constructed and operates in real time. Local array of time series points characterizing parameter chart forms. Each point on the graph the current value of the parameter and the following parameter value is formed. The time window is determined first. Array cut time window that moves along the time series. The sensor data in the process of forming a time series are used. Determination of dangerous changes in the parameters is carried out using a modified neural network.
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