this article is a comparative study of estimation power of artificial neural networks and autoregressive time series models in inflation forecasting. using 37 years iran’s inflation data, neural networks performs better on average for short horizons than autoregressive models. this study shows usefulness of early stopping technique in learning stage of neural networks for estimating time series...

the paper deals with data envelopment analysis (dea) and artificial neural network (ann). we believe that solving for the dea efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. in this paper, a new neural network model is used to estimate the inefficiency of dmus in large datasets.

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...

introduction: the native inability of nervous system to regenerate, encourage researchers to consider neural tissue engineering as a potential treatment for spinal cord injuries. considering the suitable characteristics of induced pluripotent stem cells (ipscs) for tissue regeneration applications, in this study we investigated the adhesion, viability and proliferation of neural progenitors (de...

geological facies interpretation is essential for reservoir studying. the method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. use of neural networks as classifiers is increasing in different sciences like seismic. they are computer efficient and ideal for patterns identification. they can simply learn new algori...

information on nitrate in groundwater resources requires periodic measurements are accurate. despite the measure in some areas due to sensitive social and health community are not reported. therefore, be informed of the status of each area of water quality, modeling is essential. the purpose of this study was the application of artificial neural network method for estimating nitrate and compare...

Estimation (Forecasting) of industrial production costs is one of the most important factor affecting decisions in the highly competitive markets. Thus, accuracy of the estimation is highly desirable. Hibrid Regression Neural Network is an approach proposed in this paper to obtain better fitness in comparison with Regression Analysis and the Neural Network methods. Comparing the estimated resul...

Nowadays, firms apply the merger and acquisition strategy for gaining synergy, increasing the wealth of stockholders, economics of scales, enhancing efficiency, increasing the ability to research and develop, developing the firm and decreasing the risk. Developing an optimized model with the ability to identify the effective variables on the merger and acquisition process has a significant ...

background: stem cells from human exfoliated deciduous teeth (shed) have the capability to differentiate into neural cells. neurotrophins including nerve growth factor (ngf), brain-derived neurotrophic factor (bdnf), neurotrophin-3 (nt-3), and neurotrophin-4 (nt-4) have neurogenesis, neurotrophic, or neuroprotective effects and are expressed in developing teeth. the aim of this study was to mea...