A Graph Fourier Transform Based Method for Missing Temperature Data Detection
Chien‐Cheng Tseng, Su‐Ling Lee · 2019
In this paper, a graph Fourier transform (GFT) based method for missing temperature data detection problem is presented. First, the frequency contents of GFT of temperature data are analyzed. If there is missing temperature data occurring in the sensor station, the high-frequency content increases in the spectral domain. Then, the energy ratio between high-frequency band and low-frequency band is used to develop a detector for detecting whether temperature data misses or not. The threshold value of detector is determined by computing the maximum energy ratio value of the regular daily data without missing temperature data. Finally, the real-world data measured from the weather sensor stations are used to evaluate the performance of the proposed detection method.