Data Envelopment Analysis (DEA) is a mathematic technique to evaluate the relative efficiency of a group of homogeneous decision making units (DMUs) with multiple inputs and outputs. The efficiency of each unit is measured based on its distance to the production possibility set (PPS). In this paper, the BCC model is used in output-oriented. The average return on profit as output and the covaria...

conclusions the most effected parts in asd are lateral connections of hmasd. two-sided connections which are completely symmetric become more active, and cause extra synchronization. on the other hand, due to special characteristic of two-sided connections and their ability to simulate the same phased dynamics, they cause unnatural asymmetry in children’s eeg signal. these results are consisten...

abstract: in this study, it has been tried to test the accuracy of output and hence the model efficiency in the predictions of 24 and 48 hour precipitation forecasting by choosing different schemes be assessed. therefore, in order to test the accuracy of model product, two conditions of rainfall precipitation and lack of rainfall precipitation were considered. four thresholds were taken. adapti...

background: there are many studies to investigate the effects of each interacting component of tumor-immune system interactions. in all these studies, the distinct effect of each component was investigated. as the interaction of tumor-immune system has feedback and is complex, the alternation of each component may affect other components indirectly. objective: because of the complexities of tum...

Traditional Data Envelopment Analysis (DEA) models evaluate the efficiency of decision making units (DMUs) with common crisp input and output data. However, the data in real applications are often imprecise or ambiguous. This paper transforms fuzzy fractional DEA model constructed using fuzzy arithmetic, into the conventional crisp model. This transformation is performed considering the goal pr...

In this paper, we introduce non-interest profit/loss sharing (PLS) banks into a three-period overlapping generations model. Two types, (low- and high quality) investments are assumed and capital accumulation and level of output in the steady state is considered. Then, administrative rationing is introduced to the model. It is shown that the level of capital accumulation and output in equilibriu...

optimization of machining parameters is very important and the main goal in every machining process. surface finishing prediction is a pre-requirement to establish a center for automatic machining operations. in this research, a neuro-fuzzy approach is used in order to model and predict the surface roughness in dry turning. this approach has both the learning capability of neural network and li...

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 ...

one of the biggest problems of using data envelopment analysis for the evaluation of performance is the weakness of the separability for the decision maker units. this problem is generalizable because of the lower quantity of units in comparison with the ¬input and output quantities of the model [1]. this matter considerably reveals itself in the evaluation process of 23 provincial gas companie...