Two-stage network data envelopment analysis (DEA) is widely used to evaluate efficiency of different organizations with multiple operations processes or hierarchical structures. Although existing two-stage DEA assumes systems resolve the inherent conflicts between two stages, coordination effect stages usually ignored. Recently, relation traditional “black box” has been studied from perspective...

The purpose of this research paper is to develop a framework to understand the consumer’s preference affecting variables and consumer’s perception choice in telecommunication service providers in India. The present study use a hybrid approach to access the relative efficiency based on fuzzy AHP and DEA model. The fuzzy AHP is used to determine weights of the consumer’s preference as criteria an...

Due to various seasonal and monthly changes in electricity consumption and difficulties in modeling it with the conventional methods, a novel algorithm is proposed in this paper. This study presents an approach that uses Artificial Neural Network (ANN), Principal Component Analysis (PCA), Data Envelopment Analysis (DEA) and ANOVA methods to estimate and predict electricity demand for seasonal a...

By developing the new services such as VoIP and Videoconference, using a mechanism is needed to support the quality of service of the application programs. Different models have been presented to guarantee the quality of service. Among these, the differentiated services can be mentioned which was presented by IETF. In the architecture of the differentiated services, no admission control mechani...

Data envelopment analysis (DEA) is an effective method to evaluate the relative efficiency of decision-making units (DMUs). In one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. Thi...

In this paper the performance of Artificial Neural Networks (ANNs) and Adaptive Neuro- Fuzzy Inference Systems (ANFIS) in simulating the inverse dynamic behavior of Magneto- Rheological (MR) dampers is investigated. MR dampers are one of the most applicable methods in semi active control of seismic response of structures. Various mathematical models are introduced to simulate the dynamic behavi...

Two-stage data envelopment analysis (2-DEA) is commonly used in productive efficiency analysis to estimate the effects of operational conditions and practices on performance. In this method the DEA efficiency estimates are regressed on contextual variables representing the operational conditions. We reexamine the statistical properties of the 2-DEA estimator, and find that it is statistically c...

BACKGROUND The prevalence of dog erythrocyte antigen (DEA 1) in canine population is approximately 40-60%. Often data are limited to a small number of breeds and/or dogs. The aims of this study were to evaluate frequency of DEA 1 in a large population of purebred and mongrel dogs including Italian native breeds and to recognize a possible association between DEA 1 and breed, sex, and genetic an...

Quantifying cartilage contact stress is paramount to understanding hip osteoarthritis. Discrete element analysis (DEA) is a computationally efficient method to estimate cartilage contact stresses. Previous applications of DEA have underestimated cartilage stresses and yielded unrealistic contact patterns because they assumed constant cartilage thickness and/or concentric joint geometry. The stu...