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-Reference-Cited by-同舟云学术

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

Published:2023 Issue:1 Volume:13 Page:516-526
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Xia Meng¹²^ORCID,Yang Ruifang¹^ORCID,Yin Gaofang¹,Chen Xiaowei¹^ORCID,Chen Jingsong¹²,Zhao Nanjing¹³

Affiliation:

1. Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, 350 Shushanhu Road, Hefei 230031, China

2. University of Science and Technology of China, Hefei 230026, China

3. Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China

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.

Funder

National Natural Science Foundation of China

Hefei Institutes of Physical Science, Chinese Academy of Sciences

Chinese Academy of Sciences

National Key Scientific Instrument and Equipment Development Projects of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/RA/D2RA06952K

Reference39 articles.