Detection of COD Value in Aquaculture Water by Near Infrared Spectroscopy
Journal Title: International Journal of Modern Research In Engineering & Management. - Year 2019, Vol 2, Issue 3
Abstract
Chemical oxygen demand (COD) is an important parameter of aquaculture water quality, which seriously affects the safety of aquaculture. This paper studies the COD detection technology of aquaculture water based on near infrared spectroscopy. In this paper, standard normal variate (SNV) transformation as a spectral pretreatment algorithm is used to pretreat the near infrared original spectrum of water samples, and the COD prediction model is established by partial least squares (PLS) algorithm. In order to reduce the computational complexity of the model and improve the computational speed of the model to achieve rapid detection, genetic algorithm (GA) is used to filter the spectral characteristic wavelengths, and a GA-siPLS model is established. The training set and the prediction set were tested respectively with the established model, and the prediction set Rp = 0.9924, RMSEP = 3.15; the training set Rc = 0.9937, RMSECV = 2.95. The results show that the genetic algorithm can significantly reduce the dimension of input variables, reduce the amount of calculation and ensure the prediction accuracy.
Authors and Affiliations
Zhu Chengyun
Keywords
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