in the management of river basins, prediction of river water quality is essential to maintain water quality within standard limits. this study performed a time-series analysis of the prediction of chlorine concentration and electrical conductivity time series data for the period of 1991-2005 from sefidrood river in northern iran. the seasonal prediction of chlorine and electrical conductivity t...

abstract spatial prediction of soil organic carbon is a crucial proxy to manage and conserve natural resources, monitoring co2 and preventing soil erosion strategies within the landscape, regional, and global scale. the objectives of this study was to evaluate capability of artificial neural network and multivariate linear regression models in order to predict soil organic carbon using terrain ...

introduction: to date, many prognostic models have been proposed to predict the outcome of patients with traumatic brain injuries. external validation of these models in different populations is of great importance for their generalization. the present study was designed, aiming to determine the value of crash prognostic model in prediction of 14-day mortality (14-dm) and 6-month unfavorable ou...

recently, hardware sensors are widely used in monitoring and measurement of water quality parameters. constraint of the instrument to measure some water quality parameters such as the 5-day biochemical oxygen demand (bod5), which are time consuming, causes efforts are diverted to the use of software sensors for online prediction of bod5. the main goal of this research is developing an appropria...

background: one substantial part of microarray studies is to predict patients’ survival based on their gene expression profile. variable selection techniques are powerful tools to handle high dimensionality in analysis of microarray data. however, these techniques have not been investigated in competing risks setting. this study aimed to investigate the performance of four sparse variable selec...