2023
DOI: 10.1039/d2ra06952k
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A method based on a one-dimensional convolutional neural network for UV-vis spectrometric quantification of nitrate and COD in water under random turbidity disturbance scenario

Abstract: Spectrometric quantification of nitrate and COD in water under random turbidity interference using an interpolation dataset augmentation method and one-dimensional convolutional neural network.

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Cited by 9 publications
(5 citation statements)
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“…The strength of this neural network lies in its dual-channel parallel convolutional structure, which accelerates the training speed of the network. For a comparison of the network’s training speed, please refer to our previously published article [ 38 ]. Another advantage is the lightweight nature of the network, as its training parameters are relatively small compared to those of other networks.…”
Section: Resultsmentioning
confidence: 99%
“…The strength of this neural network lies in its dual-channel parallel convolutional structure, which accelerates the training speed of the network. For a comparison of the network’s training speed, please refer to our previously published article [ 38 ]. Another advantage is the lightweight nature of the network, as its training parameters are relatively small compared to those of other networks.…”
Section: Resultsmentioning
confidence: 99%
“…To classify the plaque material on plaque sPAI data, we propose to use a one-layer CNN to transform the multi-wavelength data into a new feature space. This selection is driven by CNN’s remarkable ability to identify and capture structural patterns within the spectra, even in the presence of fluence-related spectral variations [37] , [38] . The proposed architecture is shown in Fig.…”
Section: Methodsmentioning
confidence: 99%
“…Ultraviolet spectroscopic water quality analysis technology is based on the Lambert–Beer law by combining chemometric methods to model water quality parameters that can be directly predicted for unknown concentrations. 3 This technique, known for its simplicity, rapid and convenient detection, as well as its minimal secondary pollution, is increasingly being employed to measure various parameters in water bodies, including nitrate, 4–6 nitrite, 7,8 chemical oxygen demand (COD), 9–11 and dissolved organic carbon (DOC). 12,13 Several manufacturers have developed commercial nitrate sensors, such as the SUNA, 14,15 spectrolyser, 3 and OPUS.…”
Section: Introductionmentioning
confidence: 99%