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Neural Network Improves Tunable Diode Laser Absorption Spectroscopy Quantification Accuracy

According to a research published in FUEL recently, a neural network-based absorbance recovery method was developed by a research group led by Prof. GAO Xiaoming and Prof. LIU Kun from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, to improve the accuracy of single path tunable diode laser absorption spectroscopy (TDLAS) measurement.

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