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...

Sam F. Lahidji, Steven R. Buchman, Karin Muraszko, Jeffrey W. Innis, and Catherine E. Keegan* Medical School, University of Michigan, Ann Arbor, Michigan Department of Surgery, Division of Plastic Surgery, University of Michigan, Ann Arbor, Michigan Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan Department of Human Genetics, University of Michigan, Ann Arbor, Michigan D...

considering the importance of cd and u as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the eshtehard region in iran by means of a developed artificial neural network (ann) model. the forward selection (fs) method is used to select the input variables and develop hybrid models by ann. from 45 input candidates, 13 and 14 ...

background: predicting the methane percentage of biogas is necessary for selecting the optimized technologies of using landfill biogas for energy. the aim of this study was to predict of methane fraction in biogas from landfill bioreactors by artificial neural network (ann) modeling. methods: in this study, two different systems were applied to predict the methane fraction in landfill gas as a ...

BACKGROUND Several medications have proved to be useful in preventing postoperative nausea and vomiting (PONV). However, routine antiemetic prophylaxis is not cost-effective. We evaluated the accuracy and discriminating power of an artificial neural network (ANN) to predict PONV. METHODS We analysed data from 1086 in-patients who underwent various surgical procedures under general anaesthesia...

This study develops a new approach for forecasting shear Strength of concrete beam without stirrups based on the artificial neural networks (ANN). Proposed ANN considers geometric and mechanical properties of cross section and FRP bars, and shear span-depth ratio. The ANN model is constructed from a set of experimental database available in the past literature. Efficiency of the ANN model was c...

artificial neural networks (ann) have shown to be a powerful tool for system modeling in a wide range of applications. the focus of this study is on neural network applications to data analysis in egg production. an ann model with two hidden layers, trained with a back propagation algorithm, successfully learned the relationship between the input (age of hen) and output (egg production) variabl...

Artificial neural networks (ANNs) have been successfully applied for solving a wide variety of problems. However, determining of ANN architectural and training parameter values still remains a difficult task. This paper is concerned with the usage of design of experiment (DOE) method in order to determine parameter settings of multilayer feedforward (MLFF) ANN trained with backpropagation (BP) ...

Pei-Suen Tsou , M. Asif Amin , Elena Schiopu , David A. Fox , Dinesh Khanna and Amr H. Sawalha , Division of Rheumatology, University of Michigan, Ann Arbor, MI, University of Michigan Scleroderma Program, Ann Arbor, MI, Internal Medicine, Division of Rheumatology, University of Michigan Medical Center, Ann Arbor, MI, Internal Medicine, Division of Rheumatology, University of Michigan, Ann Arbo...