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Predication of wireless communication failure in grid metering automation system based on logistic regression model

机译:基于逻辑回归模型的电网计量自动化系统无线通信故障预测

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Shenzhen power supply bureau (SZPSB) urgently need a series of methods which can analyze the cause of wireless communication fault and predict wireless communication failure, these methods can facilitate operations staff take the initiative to master the signal status, solve the problem of signal fault in time, and increase the terminal online rate. In this paper, we present a model named GCFPM (Gradient descent to iterative Calculate optimal regression coefficient in power-grid communication Failures Prediction Model) which based on Logistic Regression Algorithm (LRA), GCFPM can effectively predict the possibility of communication failure, enhance the level of acquisition terminal operations, increase the terminals online-rate and guarantee the practical effect of the electric power metering automation system (EPMAS).
机译:深圳供电局(SZPSB)迫切需要一系列能够分析无线通信故障原因并预测无线通信故障的方法,这些方法可以帮助运营人员主动掌握信号状态,解决无线通信中的信号故障问题。时间,并提高终端的在线率。本文提出了一种基于Logistic回归算法(LRA)的电网电网通信故障预测模型GCFPM(梯度下降迭代计算最优回归系数)模型,该模型可以有效地预测通信故障的可能性,增强通信效率。提高终端操作水平,提高终端在线率,保证电力计量自动化系统(EPMAS)的实际效果。

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