PPR based similarity search for gas monitoring data
基于PPR的煤矿瓦斯监测数据相似搜索方法

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.