Spatiotemporal Approaches for Quality Control and Error Correction of Atmospheric Data through Machine Learning

<div>Comparison among raw data and two corrected data (MLQC-HT and MLQC-NT). (a) Visualizing the gap between MLQC-HT and MLQC-NT (the whole time period). (b) Comparison of three types of data (extracted time period). (c) Visualizing the difference between MLQC-HT and MLQC-NT (extracted time period).</div>

Computational Intelligence and Neuroscience

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Figure 7

Figure 7: Spatiotemporal Approaches for Quality Control and Error Correction of Atmospheric Data through Machine Learning 