in this paper, it is assumed that the “decision making units“( ) are consist of positive and negative input and output. firstly, the optimistic and pessimistic models have been suggested by using negative data and then units with most productive scale size are measured in optimistic and pessimistic models. these productive values are compared with double frontiers and hurwicz’s criterion to obt...

Missing data represent an ubiquitous problem with numerous and diverse causes. Handling Missing Values (MVs) properly is a crucial issue, in particular in Machine Learning (ML) and pattern recognition. To date, the only option available for standard Neural Networks (NNs) to handle this problem has been to rely on pre-processing techniques such as imputation for estimating the missing data value...

Abstract This study firstly proposes a simpler method for evaluating one certain object’s quality with multiple criteria according to some preset evaluation threshold values that are real numbers. In life, numerous individual valuations provided distributional linguistic input information and criteria, thus they can become heterogeneous. Against this background, by using OWA weight functions we...

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 ...

the radiation power loss from a magnetically confined plasma in a stellarator has been calculated using neoclassical particle and energy fluxes in an energy balance equation. we could obtain a power loss of about 34% of the total input power by numerical calculation. this fraction of the power loss has been found to be in good agreement with the experimentally measured values of 30-40% for our ...

this paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (ccfst) stub columns under axial loading condition based on artificial neural networks (anns) by using a large wide of experimental investigations. the input parameters were selected based on past studies such as outer diameter of column, compressive strength...