abstract   background : leukemia is one of the mostcommon cancers in children, comprising more than a third of all childhood cancers. newly affected patients in usa are estimated as 10100cases, and if these cases are diagnosed late or proper treatment is not applied, then it can be mortal. because rapid and proper diagnosis of leukemia based on clinical or medicinal findings (without biopsy) is...

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 ...

objective(s): this study aims to evaluate and predict the thermal conductivity of iron oxide nanofluid at different temperatures and volume fractions by artificial neural network (ann) and correlation using experimental data. methods: two-layer perceptron feedforward artificial neural network and backpropagation levenberg-marquardt (bp-lm) training algorithm are used to predict the thermal cond...

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are...

The mortality rate due to breast cancer is increasing, for five minute a women dies worldwide. Mammogram is one which reduces the death rate by early diagnosis and regular screening. This paper hypothesize a consolidate approach of FPGA implementation for automatic detection of breast cancer and classification of the tumor by adopting 2D discrete wavelet transform and artificial neural network ...

In this research, a hybrid wavelet-artificial neural network (WANN) and a geostatistical method were proposed for spatiotemporal prediction of the groundwater level (GWL) for one month ahead. For this purpose, monthly observed time series of GWL were collected from September 2005 to April 2014 in 10 piezometers around Mashhad City in the Northeast of Iran. In temporal forecasting, an artificial...

The main goal of the present work is to decrease the computational burden for optimum design of steel frames with frequency constraints using a new type of neural networks called Wavelet Neural Network. It is contested to train a suitable neural network for frequency approximation work as the analysis program. The combination of wavelet theory and Neural Networks (NN) has lead to the developmen...

In this paper, a classification method for respiratory sounds (RSs) in patients with asthma and in healthy subjects is presented. Wavelet transform is applied to a window containing 256 samples. Elements of the feature vectors are obtained from the wavelet coefficients. The best feature elements are selected by using dynamic programming. Grow and Learn (GAL) neural network is used for the class...

Abstract— This paper considers two important classification algorithms for to classify several power quality disturbances. Artificial Neural Network (ANN) and support vector machine (SVM). The last one is a novel algorithm that has shown good performance in general patterns classification. Nevertheless, Multilayer Perceptron Artificial Neural Network (MLPANN) is the most popular and most widely...