In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used ...

classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. this paper proposes a three module system for classification of electrocardiogram (ecg) beats. these modules are: denoising module, feature extraction module and a classification module. in the first module the stationary wavelet transform (swf) is used for noise reduction of ...

Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...

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...

Abstract Forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. This paper studies load consumption modeling in Hamedan city province distribution network by applying ESN neural network. Weather forecasting data such as minimum day temperature, average day temp...

important parameters on apple drying process are investigated experimentally and modeled employing artificial neural network and neuro-taguchi's method. experimental results show that the apple drying curve stands in the falling rate period of drying. temperature is the most important parameter that has a more pronounced effect on drying rate than the other two parameters i.e. air velocity and ...

The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...

Stochastic gradient descent (SGD), which updates the model parameters by adding a local gradient times a learning rate at each step, is widely used in model training of machine learning algorithms such as neural networks. It is observed that the models trained by SGD are sensitive to learning rates and good learning rates are problem specific. We propose an algorithm to automatically learn lear...

The aim of this paper is to present a model based on feed forward neural networks to recognize bad credit customers in Saman Bank. To find an appropriate structure for the proposed neural network model, three different strategies called quick, dynamic and multiple strategies are investigated. The registered data of credit customer in Saman Bank from 2000 to 2008 year is used. To prevent models ...

results overall, the prevalence of unwanted pregnancies was 32.3%. the performance of the models based on the area under the roc curve as the indicator was as follows: artificial neural networks (0.741), decision tree (0.731), and logistic regression (0.712). the highest sensitivity level belonged to the decision tree (73.5%), and the highest specificity level belonged to the artificial neural ...