This paper studies the application of principal component analysis, multiple polynomial regression, and artificial neural network ANN techniques to the quantitative analysis of binary mixture of dye solution. The binary mixtures of three textile dyes including blue, red and yellow colors were analyzed by PCA-Multiple polynomial Regression and PCA-Artificial Neural network PCA-ANN methods. The o...

The collapse settlement of granular soil, which brings about considerable deformations, is an important issue in geotechnical engineering. Several factors are involved this phenomenon, makes it difficult to predict. present study aimed develop a model predict the and coefficient stress release sandy gravel soil through evolutionary polynomial regression (EPR). To achieve this, dataset containin...

Treatment effect estimates in regression discontinuity (RD) designs are often sensitive to the choice of bandwidth and polynomial order, two important ingredients widely used local methods. While Imbens Kalyanaraman Calonico, Cattaneo, Titiunik provided guidance on bandwidth, sensitivity order still poses a conundrum RD practitioners. It is understood econometric literature that applying argume...