Abstract
The pesticides and active pharmaceutical compounds in water can potentially causedamage, including theincreased cancer risk; liver, and kidney. A quantitative structure–retention relationship (QSRR) was developed using the partial least square (PLS), Kernel PLS (KPLS), and Levenberg-Marquardt artificial neural network (L-M ANN) approach for chemometrics study. The data contained retention time (RT) of the 87 pesticides and active pharmaceutical compounds in wastewater and river waters. Genetic algorithm was employed as a factor selection procedure for PLS and KPLS modeling methods. The results showed that, the GA-PLS descriptors are selected for L-M ANN. Finally a model with a low prediction error and a good correlation coefficient was obtained by L-M ANN.
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.
