Forecasting of UV-Vis absorbance time series using artificial neural networks combined with principal component analysis

Abstract

This work proposes a methodology for the forecasting of online water quality data provided by UV-Vis spectrometry. Therefore, a combination of principal component analysis (PCA) to reduce the dimensionality of a data set and artificial neural networks (ANNs) for forecasting purposes was used. The results obtained were compared with those obtained by using discrete Fourier transform (DFT). The proposed methodology was applied to four absorbance time series data sets composed by a total number of 5705 UV-Vis spectra. Absolute percentage errors obtained by applying the proposed PCA/ANN methodology vary between 10% and 13% for all four study sites. In general terms, the results obtained were hardly generalizable, as they appeared to be highly dependent on specific dynamics of the water system; however, some trends can be outlined. PCA/ANN methodology gives better results than PCA/DFT forecasting procedure by using a specific spectra range for the following conditions: (i) for Salitre wastewater treatment plant (WWTP) (first hour) and Graz West R05 (first 18 min), from the last part of UV range to all visible range; (ii) for Gibraltar pumping station (first 6 min) for all UV-Vis absorbance spectra; and (iii) for San Fernando WWTP (first 24 min) for all of UV range to middle part of visible range.

Arima as a forecasting tool for water quality time series measured with UV-Vis spectrometers in a constructed wetland

“…Spectro::lyser TM UV-Vis waterproof spectrometers, 65 centimeters long by 44 millimeters wide, are used to conduct the present research. Primarily used to record light attenuation (absorbance) on-line continuously (one signal per minute), these spectrometers are equipped with a xenon light of wavelength 200 nm to 750 nm at 2.5 nm intervals (Plazas-Nossa & Torres, 2013; Plazas-Nossa, Torres, Gruber, & Hofer, 2014). The spectrometers are located at the input (affluent) and output (effluent) of the constructed wetland.…”

Applications of Online UV-Vis Spectrophotometer for Drinking Water Quality Monitoring and Process Control: A Review

“…A web interface of the system works as a control centre constantly checking for anomalies in water quality based on automatic data evaluation. Maintenance can be reduced, as remote checking of water quality is available [81].…”

“…Data analytics of water quality data using the UV-Vis instruments combined with data platforms have capabilities to automatically analyse and correct data in real-time and then predict to improve water quality monitoring and process control. Since each water quality detection method based on the UV-Vis spectra has its strengths and drawbacks, multiple methods should be conducted to assess their performance and analyse which methods can be used to construct decision support tools for the optimisation of a particular WTP [81]. The future application of the UV-Vis instrument also includes exploring the use of raw spectra as inputs to determine the measurements of other water quality parameters.…”