in this work, quantitative structure-property relationship (qspr) approaches were used to predict the redox potential of 42 phenolic antioxidants. the structures of all compounds optimized by the am1 semi-empirical method and then a large number of molecular descriptors were calculated for each compound in the data set. subsequently, stepwise multilinear regression was applied to select the mos...

Most of the land use change modelers have used to model binary land use change rather than multiple land use changes. As a first objective of this study, we compared two well-known LUC models, called classification and regression tree (CART) and artificial neural network (ANN) from two groups of data mining tools, global parametric and local non-parametric models, to model multiple LUCs. The ca...

our study performed upon an extended series of 28 compounds of 1,2,4-triazole derivativesthat demonstrate substantial in vitro antimicrobial activities by serial plate dilution method,using quantitative structure-activity relationship (qsar) methods that imply analysis ofcorrelations and multiple linear regression (mlr); a significant collection of moleculardescriptors was used e.g., edge adjac...

the cold climate is a favorable parameter for the development of tension cracks and decrease of rock brittleness. therefore, this paper attempts to investigate the hamekasi porous limestone in order to predict the brittleness indices during freeze-thaw cycles. the freeze–thaw test was executed for one cycle including 16 h of freezing, and 8 h of thawing. the geo mechanical properties and brittl...

In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...