The paper deals with Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN). We believe that solving for the DEA efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. In this paper, a new neural network model is used to estimate the inefficiency of DMUs in large datasets.

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-...

abstract erosion and sedimentation are the most complicated problems in hydrodynamic which are very important in water-related projects of arid and semi-arid basins. for this reason, the presence of suitable methods for good estimation of suspended sediment load of rivers is very valuable. solving hydrodynamic equations related to these phenomenons and access to a mathematical-conceptual model ...

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 ...

in recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. for solving this problem, some approaches have been presented. recently, the artificial neural networks (ann) as a heuristic method has more applications for this propose. in this paper, short-term (1 hour) and mid-term (24...

prediction of the heavy metals in the groundwater is important in developing any appropriate remediation strategy. this paper attempts to predict heavy metals (pb, zn and cu) in the groundwater from arak city, using artificial neural network (ann) algorithm by taking major elements (hco3, so4) in the groundwater from arak city. for this purpose, contamination sources in the groundwater were rec...

the quantitative structure-retention relationship (qsrr) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. the genetic algorithm (ga) was employed to select the variables that resulted in the best-fitted models. after the variables were selected, the linear multi...