background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...

A priori wirelength prediction is an important and often addressed problem in physical design with numerous and high impact applications. In the last four decades a wide spectrum of insightful and sophisticated techniques for a priori wirelength prediction have been developed. In addition, highly accurate predictions and models have been reported for average wirelength and wirelength distributi...

this study predicts corporate bankruptcy five years before its occurrence using financial ratios introduced in altman’s z-score model and current ratio. three estimation methods namely; liner probability, logit and probit models have chosen for model estimation. the sample contains 134 companies in tehran stock exchange during 2003. the precision of prediction of the estimated models for the ma...

background: data mining (dm) is an approach used in extracting valuable information from environmental processes. this research depicts a dm approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond (wsp) in birjand, a city in eastern iran. methods: multiple regression (mr) and neural network (nn) models were examined us...

due to the importance of the import management, this study applies generalized ardl approach to estimate midas regression for wheat import value and to compare the accuracy of forecasts with those competed by the regression with adjusted data model. mixed frequency sampling models aim to extract information with high frequency indicators so that independent variables with lower frequencies are ...

Dynamic modulus characterizes the viscoelastic behavior of asphalt materials and is the most important input parameter for design and rehabilitation of flexible pavements using Mechanistic–Empirical Pavement Design Guide (MEPDG). Laboratory determination of dynamic modulus is very expensive and time consuming. To overcome this challenge, several predictive models were developed to determine dyn...

soil moisture retention curve (smrc) is an important soil property which expresses reaction between matric potential and moisture of soil. direct measurement of soil matric potential and moisture is labour- and time-consuming. in order to prevail this problem, indirect methods are used for smrc prediction. pedotransfer functions (ptfs) are one of these indirect methods. this study was carried o...

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...

A quantitative structure-activity relationship (QSAR) study was conducted for the prediction of inhibitory activity of 1-phenyl[2H]-tetrahydro-triazine-3-one analogues as inhibitors of 5-Lipoxygenase. The inhibitory activities of the 1-phenyl[2H]-tetrahydro-triazine-3-one analogues modeled as a function of molecular structures using chemometrics methods such as multiple linear regression (MLR) ...