Abstract
Pesticide residues have become a global concern because of the threaten to human health. To realize the non-destructive detection of the pesticides containing in the drinking water, this work introduces multiple layers neural network algorithm to predict multiple kinds of pesticides with a single model of fluorescence spectra. To demonstrate the effectiveness of the algorithm, four traditional pesticides (zhongshengmycin, paclobutrazol, boscalid and pyridaben) were dissolved in the drinking water to achieve different concentrations and then the fluorescence spectra of these samples were measured. A model with four hidden layers was built using these fluorescence spectra. 50 samples were used to validate the model and the results demonstrated the feasibility of the model.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
