Background: Diabetes and hypertension are important non-communicable diseases and their prevalence is important for health authorities. The aim of this study was to determine the predictive precision of the bivariate Logistic Regression (LR) and Artificial Neutral Network (ANN) in concurrent diagnosis of diabetes and hypertension. Methods: This cross-sectional study was performed with 12000 ...

Emissions from motor vehicles need to be predicted fairly accurately to ensure an appropriate air quality management plan. This research work explores the use of a nonparametric regression algorithm known as the multivariate adaptive regression splines (MARS) in comparison with the artificial neural networks (ANN) for the purpose of best approximation of the relationship between the input and o...

background: municipal solid waste (msw) is the natural result of human activities. msw generation modeling is of prime im­portance in designing and programming municipal solid waste management system. this study tests the short-term pre­diction of waste generation by artificial neural network (ann) and principal component-regression analysis. methods: two forecasting techniques are presented in...

quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (fa-mlr), principle component regression analysis (pcra), and genetic algorithm-partial least squares ga-pls. the fa-mlr describes the effect of geometrical and quantum indices on enzyme inhibition act...

Fire has significant effects on the residual resistance of steel structures. It is necessary to accurately clarify its Q690 HSS plate girders, which have been widely used. In this paper, ultimate and effective service girders after a fire are obtained using material tests finite element (FE) analysis including parametric studies, where data 210 models were collected. The four key parameters (hw...

a novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (wds) for the purpose of its hydraulic model calibration is presented. the problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. the objectives are to maximise the calibrated model accuracy and to minimise the number of sampling d...

Objective:Predictions of hospital charges for cancer patients are very important, because they provide a basis for allocating medical resources in the hospital and for establishing national medical policies. But previous studies to predict hospital charges were mainly based on statistical analysis, which has used only a small aspect among huge medical data so that the prediction power was limit...