基于PPR的煤矿瓦斯监测数据相似搜索方法

研究基于时间序列相似搜索技术的煤矿瓦斯涌出分析新途径，提出基于PPR的煤矿瓦斯监测数据相似搜索方法。实验采用玉华煤矿的真实煤矿瓦斯监测数据，评价指标为信息损失量及相似查询效率。与基于离散傅立叶变换(DFT)和离散小波变换(DWT)的时间序列相似搜索算法的对比实验显示：在相同压缩比下，3种方法的信息损失相近；但是基于PPR的相似搜索算法的平均查询效率分别比基于DFT和基于DWT方法高32%和34%。因此PPR算法适合用于瓦斯监测数据相似搜索。

PPR based similarity search for gas monitoring data

A Piecewise Polynomial Representation (PPR) based similarity search approach for time series data in coal well gas monitoring was proposed. For experiments, sample data were real gas monitoring data obtained from Yuhua Coal Mine, and evaluation criterions were information loss and mean search efficiency. Experimental results compared with the performance of Discrete Fourier Transform (DFT) based approach and Discrete Wavelet Transform (DWT) based approach show: in the condition of the same compress rate, values of information loss of PPR, DFT and DWT based approaches are very close to each other; Whereas, mean search efficiency of PPR based approach is 32% higher than that of DFT based approach, and 34% higher than that of DWT based approach respectively. Therefore, PPR based approach is more suitable for similarity search of gas monitoring data.