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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网格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:深圳市电源局(SZPSB)迫切需要一系列方法,可以分析无线通信故障的原因并预测无线通信故障,这些方法可以促进运营人员主动掌握信号状态,解决信号故障问题时间,并增加终端在线率。在本文中,我们介绍了一个名为GCFPM的模型(梯度下降到迭代计算的电网通信故障预测模型中的最佳回归系数),基于逻辑回归算法(LRA),GCFPM可以有效地预测通信故障的可能性,增强采集终端运营水平,增加终端在线速率,保证电力计量自动化系统(EPMAS)的实际效果。

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