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...

Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...

Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...

an artificial neural network (ann) model is developed for the analysis, simulation, and prediction of the austenite reversion in the thermo-mechanical treatment of 304l austenitic stainless steel. the results of the ann model are in good agreement with the experimental data. the model is used to predict an appropriate annealing condition for austenite reversion through the martensite to austeni...

abstract evapotranspiration as one of the important elements in agriculture has a considerable role in water resource management. therefore, using a more exact estimation method is an essential step of agricultural development, especially in arid semi-arid area. in this research, in order to exact estimate of garlic evapotranspiration using lysimeteric data, an artificial neural network (ann) m...

Background: Forecasting of air pollutants has become a popular topic of environmental research today. For this purpose, the artificial neural network (AAN) technique is widely used as a reliable method for forecasting air pollutants in urban areas. On the other hand, the evolutionary polynomial regression (EPR) model has recently been used as a forecasting tool in some environmental issues. In ...

The paper proposes an artificial neural network (ANN)-based strategy for identification of reduced-order dynamic equivalents of power systems. This large-signal model is formulated in continuous-time and is therefore compatible with standard models of power system components. In a departure from previous works on the subject, we do not postulate a particular model structure for the equivalent, ...

the decisions made in the planning phase of a building project greatly affect its future operation and maintenance (o&m;) cost. recognizing the o&m; cost of condominiums’ common facilities as a critical issue for home owners, this research aims to develop an artificial neural network (ann) o&m; cost prediction model to assist developers and architects in effectively assessing the impacts of the...

background: we designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the artificial neural network (ann). materials and methods: the ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. each patient’s record consisted of 6 s...

Forecasting financial markets is an important issue in finance area and research studies. On one hand, the importance of prediction, and on the other hand, its complexity, have led to huge number of researches which have proposed many forecasting methods in this area. In this study, we propose a hybrid model including Wavelet Transform, ARMA-GARCH and Artificial Neural Network (ANN) for single-...