@ARTICLE{Cui_Zhiwen_Similarity_2022,
 author={Cui, Zhiwen and Li, Wenjun and Yu, Sisi and Jin, Minjun},
 volume={vol. 29},
 number={No 2},
 journal={Metrology and Measurement Systems},
 pages={283-300},
 howpublished={online},
 year={2022},
 publisher={Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation},
 abstract={Different temperature sensors show different measurement values when excited by the same dynamic temperature source. Therefore, a method is needed to determine the difference between dynamic temperature measurements. This paper proposes a novelty approach to treating dynamic temperature measurements over a period of time as a temperature time series, and derives the formula for the distance between the measurement values using uniformsampling within the time series analysis. The similarity is defined in terms of distance to measure the difference. The distance measures were studied on the analog measurement datasets. The results show that the discrete Fréchet distance has stronger robustness and higher sensitivity. The two methods have also been applied to an experimental dataset. The experimental results also confirm that the discrete Fréchet distance performs better.},
 type={Article},
 title={Similarity analysis of dynamic temperature measurements},
 URL={http://journals.pan.pl/Content/123575/PDF-MASTER/a04.pdf},
 doi={10.24425/mms.2022.140036},
 keywords={dynamic temperature, temperature time series, similarity measure, distance measurement},
}