In this work, artificial neural network (ANN) has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures was employed. These systems consist of 777 data points generally containing hydrocar...

abstract process of evapotranspiration (eto) is a major component of the hydrologic cycle that its accurate estimation plays an important role to achieve sustainable development in water balance, irrigation system design and planning and management of water resources. being a function of different metrological parameters and their interactions, evapotranspiration is a complex, nonlinear phenome...

applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. artificial neural networks (ann) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. most ann models applied in economics use the gradient descent method as their learning algorithm. however, t...

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 ...

In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...

the objective of this paper is to develop an artificial neural network (ann) model which can beused to predict temperature rise due to climate change in regional scale. in the present work data recorded overyears 1985-2008 have been used at training and testing steps for ann model. the multilayer perceptron(mlp) network architecture is used for this purpose. three applied optimization methods a...

In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...

an artificial neural network (ann) approach was used to model the wheat production. from an extensive data collection involving 40 farms in canterbury, new zealand, the average wheat production was estimated at 9.9 t ha-1. the final ann model developed was capable of predicting wheat production under different conditions and farming systems using direct and indirect technical factors. after exa...