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Research on the prediction model of UV spectral water quality parameters based on INFO-LSSVM
Summary
Researchers developed an INFO-LSSVM prediction model combining UV-visible absorption spectroscopy with an intelligent optimization algorithm to rapidly detect nitrate nitrogen and nitrite nitrogen concentrations in water. The model demonstrated improved accuracy and speed compared to conventional approaches such as GA-LSSVM, offering a practical tool for real-time water quality monitoring.
In order to meet the requirements of precision and rapid detection of water quality parameters, UV- visible absorption spectroscopy was used for the measurement and INFO-LSSVM was proposed for predic- tive modelling. The common nitrate nitrogen (NO 3 -N) and nitrite nitrogen (NO 2 -N) in water quality testing as the solution to be measured, the UV-visible absorption spectral data filtering, spectral data integration, the establishment of INFO-LSSVM nonlinear prediction model; comparison of GA-LSSVM, PSO-LSSVM and LSSVM algorithm models, the results show that the INFO-LSSVM prediction model is effective, and pro- vides a good solution for water quality testing. LSSVM prediction model is effective and provides new re- search value for water quality detection.