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A multiple linear regression data predicting method using correlation analysis for wireless sensor networks

机译:基于相关分析的无线传感器网络多元线性回归数据预测方法

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For there are too many drawbacks like excessive input variables, high computational complexity and low efficiency in evaluation methods of missing data for wireless sensor network, A Multiple-Regression evaluation method based on correlation analysis was proposed in this paper. First, the sensor data of the wireless sensor networks was correlatively analyzed, and most correlation sensor data was explored. Then the sensor data was used as input of the multiple linear Regression model and evaluation method. In the experimental stage, the sensor temperature data of actual wireless sensor network has been used to test this method. Experiment results show that the scheme is efficient with low prediction error, thus it owns practical value and can be used to evaluate the missing data in wireless sensor networks.
机译:针对无线传感器网络缺失数据评估方法存在输入变量过多,计算复杂度高,效率低等缺点,提出了一种基于相关分析的多元回归评估方法。首先,对无线传感器网络的传感器数据进行相关分析,并探索大多数相关传感器数据。然后将传感器数据用作多元线性回归模型和评估方法的输入。在实验阶段,实际无线传感器网络的传感器温度数据已用于测试该方法。实验结果表明,该方案有效且预测误差小,具有实用价值,可用于评估无线传感器网络中的丢失数据。

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