many efforts have been made to model the the hot deformation (dynamic recrystallization) flow curves of different materials. phenomenological constitutive models, physical-based constitutive models and artificial neural network (ann) models are the main methods used for this purpose. however, there is no report on the modeling of warm deformation (dynamic spheroidization) flow curves of any kin...

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 research, both resource allocation and reactive resource allocation problems in multi-server dynamic pert networks are analytically modeled, where new projects are expected to arrive according to a poisson process, and activity durations are also known as independent random variables with exponential distributions. such system is represented as a queuing network, where multi servers at ...

Measuring the efficiency of real businesses is not a simple task, because a real business may involve several processes and sub-processes, forming a very complicated dynamic network of interactions. In this paper, a customized dynamic network data envelopment analysis (NDEA) model is proposed to measure the efficiency of the sub-processes in a real business. The proposed dynamic NDEA model is f...

totoday’s market place is increasingly dynamic and volatile. in this area supply network issues recently have attracted a lot of attention from industrial practitioners and academics worldwide. chaos theory is the study of complex, nonlinear, dynamic systems. for chaotic systems, a tiny change in conditions may result in an enormous change in system output, whereas substantial changes in condit...

Dynamic network data envelopment analysis (DNDEA) has attracted a lot of attention in recent years. On one hand the available models in DNDEA evaluating the performance of a DMU with interrelated processes during specified multiple periods but on the other hand they can only measure the efficiency of dynamic network structure when a supply chain structure present. For example, in the banking in...

in this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. cgam problem, a benchmark in cogeneration systems, is chosen as a casestudy. thermodynamic model includes precise modeling of the whole plant. for simulation of the steadysate behavior, the static neural network is applied. then using dynamic neural network, plant is...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...