Estimation of Water Quality Parameters Using Regression Model with KNN and BPNN

Abstract: In this paper, we are monitoring and estimating the pollutant typically on the spectral response or scattering of water reflections. In this present study we proposed a new method that to detect pollutants and we determine water quality parameters based on the theory of texture analysis. Here the GLCM(Gray Level of Co-occurrence Matrix)is used to estimate several texture Parameter-Contract, Correlation, Energy, Homogeneity there parameters are used for estimate a regression model with WQPs(Water Quality Parameters standard) the KNN & BPNN are used to generalize the water quality estimates of all segmented image. By using situ measurements & IKOMOS data, the results can be shows that texture parameters & remote sensing can monitor & predict the distribution of WQP in large rivers.

Keywords: Water parameters, KNN, BPNN, Texture