Drug resistance enables cancer cells to break away from cytotoxic effect of anticancer drugs. Identification of resistant phenotype is very important because it can lead to effective treatment plan. There is an interest in developing classifying models of resistance phenotype based on the multivariate data. We have investigated a vibrational spectroscopic approach in order to characterize a...

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...

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...

Data Envelopment Analysis (DEA) has two fundamental approaches for assessing theefficiency with different characteristics; radial and non-radial models. This paper isconcerned the non-radial model of Russell which is a non linear model. Conventional DEAfor a large dataset with many inputs/outputs would require huge computer resources in termsof memory and CPU time. Artificial Neural Network (AN...

The aim of this study was to estimate suspended sediment by the ANN model, DT with CART algorithm and different types of SRC, in ten stations from the Lorestan Province of Iran. The results showed that the accuracy of ANN with Levenberg-Marquardt back propagation algorithm is more than the two other models, especially in high discharges. Comparison of different intervals in models showed that r...

soil hydraulic properties such as saturated and unsaturated hydraulic conductivity play an important role in environmental research. since direct measurement of these soil hydraulic properties is time-consuming and costly, indirect methods such as pedotransfer functions and artificial neural networks (ann) were developed based on readily available parameters. in this study, the use of ann to pr...

The quantitative structure-retention relationship (QSRR) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. The genetic algorithm (GA) was employed to select the variables that resulted in the best-fitted models. After the variables were selected, the linear multi...

An artificial neural network (ANN) based helicopter identification system is proposed. The feature vectors are based on both the tonal and the broadband spectrum of the helicopter signal. ANN pattern classifiers are trained using various parametric spectral representation techniques. Specifically, linear prediction, reflection coefficients, cepstrum, and line spectral frequencies (LSF) are comp...