in this work quantitative structure activity relationship (qsar) methodology was applied for modeling and prediction of cellular response to polymers that have been designed for tissue engineering. after calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regressions (mlr) and artificial neural network (ann) methods. the root m...

a new retrofit targeting procedure, based on pinch technology has been developed. the new procedure considers existing structure of a given network and finds the most compatible configuration with the network. to achieve this aim, the procedure uses a linear programming technique that maximize the compatibility. good compatibility between old and new networks helps to make the best use of capit...

in this study, we focused on the gait of parkinson’s disease (pd) and presented a gray box model for it. we tried to present a model for basal ganglia structure in order to generate stride time interval signal in model output for healthy and pd states. because of feedback role of dopamine neurotransmitter in basal ganglia, this part is modelled by “elman network”, which is a neural network stru...

As we know, in evaluating of DMUs some of them might be efficient, so ranking of them have a high significant. One of the ranking methods is cross-efficiency. Cross efficiency evaluation in data envelopment analysis (DEA) is a commonly used skill for ranking decision making units (DMUs). Since, many studies ignore the intra-organizational communication and consider DMUs as a black box. For sign...

binary decision diagram (bdd) is a data structure proved to be compact in representation and efficient in manipulation of boolean formulas. using binary decision diagram in network reliability analysis has already been investigated by some researchers. in this paper we show how an exact algorithm for network reliability can be improved and implemented efficiently by using cudd - colorado univer...

In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in Data Envelopment Analysis(DEA). The proposed neural network model is derived from an unconstrained minimization problem. In theoretical aspect, it is shown that the proposed neural network is stable in the sense of lyapunov and globally convergent. The proposed model has a single-laye...

nowadays, due to increasing the complexity of ic engines, calibration task becomes more severe and the need to use surrogate models for investigating of the engine behavior arises. accordingly, many black box modeling approaches have been used in this context among which network based models are of the most powerful approaches thanks to their flexible structures. in this paper four network base...