Abstract We propose an improved wavelet threshold de-noising algorithm combined with adaptive noise complete set empirical mode decomposition(CEEMDAN) for the de-noising of groundwater temperature observation data. After using this method and the traditional denoising method to denoise the simulation signal respectively, we find that the proposed denoising method has better performance, and shows better effects than the traditional single filtering method in processing the actually collected groundwater temperature data containing noise and abnormal mutation.
SUN Dexian,OU Tonggeng. Research on Denoising Method of Groundwater Temperature Observation Data Using the Improved Wavelet Threshold Denoising Combined with CEEMDAN[J]. jgg, 2023, 43(4): 435-440.
SUN Dexian,OU Tonggeng. Research on Denoising Method of Groundwater Temperature Observation Data Using the Improved Wavelet Threshold Denoising Combined with CEEMDAN[J]. jgg, 2023, 43(4): 435-440.