Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple inputs and multiple outputs. DEA-based Malmquist productivity index measures the productivity change over time. We propose a dynamic DEA model involving network structure in each period within the framework a DEA. We have previously published the network DEA (NDEA) and the dynamic DEA ...

in this paper we present the problem of designing a three level hub center network. in our network, the top level consists of a complete network where a direct link is between all central hubs.  the second and third levels consist of star networks that connect the hubs to central hubs and the demand nodes to hubs and thus to central hubs, respectively. we model this problem in an incomplete net...

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...

In this paper statistical and time series models are used for determining the random drift of a dynamically Tuned Gyroscope (DTG). This drift is compensated with optimal predictive transfer function. Also nonlinear neural-network and fuzzy-neural models are investigated for prediction and compensation of the random drift. Finally the different models are compared together and their advantages a...

Rainfall-runoff relationship is very important in many fields of hydrology such as water supply and water resourcemanagement and there are many models in this field. Among these models, the Artificial Neural Network (ANN) wasfound suitable for processing rainfall-runoff and opened various approaches in hydrological modeling. In addition,ANNs are quick and flexible approaches which provide very ...