in this article different types of artificial neural networks (ann) were used for cntfet (carbon nanotube transistors) simulation. cntfet is one of the most likely alternatives to silicon transistors due to its excellent electronic properties. in determining the accurate output drain current of cntfet, time lapsed and accuracy of different simulation methods were compared. the training data for...

static deformation modulus is recognized as one of the most important parameters governing the behavior of rock masses. predictive models for the mechanical properties of rock masses have been used in rock engineering because direct measurement of the properties is difficult due to time and cost constraints. in this method the deformation modulus is estimated indirectly from classification syst...

This paper presents artificial neural network (ANN)-based models for forecasting precipitation, in which the training parameters are adjusted using a parameter automatic calibration (PAC) approach. A classical ANN-based model, the multilayer perceptron (MLP) neural network, was used to verify the utility of the proposed ANN–PAC approach. The MLP-based ANN used the learning rate, momentum, and n...

Many computer models for predicting the risk of prostate cancer have been developed including for prediction of biochemical recurrence (BCR). However, models for individual BCR free probability at individual time-points after a BCR free period are rare. Follow-up data from 1656 patients who underwent laparoscopic radical prostatectomy (LRP) were used to develop an artificial neural network (ANN...

In this work the electrooxidation half-wave potentials of some Benzoxazines were predicted from their structural molecular descriptors by using quantitative structure-property relationship (QSAR) approaches. The dataset consist the half-wave potential of 40 benzoxazine derivatives which were obtained by DC-polarography. Descriptors which were selected by stepwise multiple selection procedure ar...

in this study greenhouse tomato production was investigated from energy consumption and greenhouse gas (ghg) emission point of views. moreover, artificial neural networks (anns) and adaptive neuro-fuzzy inference systems (anfis) were employed to model energy consumption for greenhouse tomato production. total energy input and output were calculated as 1316.14 and 281.1 gj/ha. among the all ener...

solar radiation data play an important role in solar energy relevant researches. these data are not available for some locations due to the absence of the meteorological stations. therefore, solar radiation data have to be predicted by using solar radiation estimation models. this study presents an integrated artificial neural network (ann) approach for estimating solar radiation potential over...

in this work, artificial neural network (ann) has been employed to propose a practical model forpredicting the surface tension of multi-component mixtures. in order to develop a reliable modelbased on the ann, a comprehensive experimental data set including 15 ternary liquid mixtures atdifferent temperatures was employed. these systems consist of 777 data points generally containinghydrocarbon ...

pearl millet has tolerance to harsh growing conditions such as drought. it is at least equivalent to maize and generally superior to sorghum in protein content and metabolizable energy levels. thus it is of importance for poultry feeding. amino acid (aa) determination is expensive and time consuming. therefore nutritionists have prompted a search for alternatives to estimate aa levels. traditio...