最后通过实验验证表明应用限幅滤波算法进行WSN数据预处理具有更好的疏失误差查找准确率，误报率更低。
The experiments verify that the use of amplitude-limiting filtering algorithm WSN data pretreatment has better leverage error rate, the rate of false positives search even lower.
给出了检验疏失误差是否存在的符号检验法和游程数检验法。并给出了存在疏失误差时如何调整实验数据协方差矩阵的方法。
The methods of sign test and runs number test of negligence error and adjustment of experimental covariance matrix are given in the work.
采用分布图法抑制干扰因素，消除疏失误差并利用算术平均值与分批估计相结合的方法对数据进行融合处理，得到所需的测量结果。
The method to reject and calculate the mistake error of the transformer /low voltage user remote monitoring and the principle of data mining were present.
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