Online water quality monitoring based on UV-Vis spectrometry and artificial neural networks in a river confluence near Sherfield-on-Loddon.

ABSTRACT: Water quality monitoring is very important in agricultural catchments. UV-Vis spectrometry is widely used in place of traditional analytical methods because it is cost effective and fast and there is no chemical waste. In recent years, artificial neural networks have been extensively studied and used in various areas. In this study, we plan to simplify water quality monitoring with UV-Vis spectrometry and artificial neural networks. Samples were collected and immediately taken back to a laboratory for analysis. The absorption spectra of the water sample were acquired within a wavelength range from 200 to 800 nm. Convolutional neural network (CNN) and partial least squares (PLS) methods are used to calculate water parameters and obtain accurate results. The experimental results of this stud

SUBMITTER: Zhang H 

PROVIDER: S-EPMC9349112 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature