through the last three decades different seismological and engineering approaches for the generation of artificial earthquakes have been proposed. selection of an appropriate method for the generation of applicable artificial earthquake accelerograms (aeas) has been a challenging subject in the time history analysis of the structures in the case of the absence of sufficient recorded accelerogra...

Stock market forecasting has attracted so many researchers and investors that ‎many studies have been done in this field. These studies have led to the ‎development of many predictive methods, the most widely used of which are ‎machine learning-based methods. In machine learning-based methods, loss ‎function has a key role in determining the model weights. In this study a new loss ‎function is ...

In this paper, a new method for estimation of transient parameters of transformer high voltage winding using the artificial neural networks (ANN) is proposed. An ANN with different structures is trained for parameters estimation of transformer winding Detailed Model that data is generated by analysis of frequency response. It is shown that feed-forward back propagation network with Levenberg-Ma...

This study was conducted to rate the land characteristics of corn in hot areas based on artificial neural networks and regression models. For this purpose, 63 corn fields were selected in southern Iran. In each farm, a pedon was excavated, described and sampled. A questionnaire was completed for each farm. A stepwise regression model was used to study the relationship between land characteristi...

This paper presents an alternative approach using the differential logic associated to Artificial Neural Networks (ANNs) in order to distinguish between inrush currents and internal faults in the protection of power transformers. The Alternative Transients Program (ATP) has been chosen as the computational tool to simulate a power transformer under fault and energization situations. The Radius ...

abstract: this paper represents a novel use of artificial neural networks in medical science. the proposed technique involves training a multi layer perceptron (mlp) (a kind of artificial neural network) with a bp learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from h1 machine. the blood test parameters and ...

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...

The paper describes a novel neural model to estimate electrical loss in transformer according to the energy consumption (load curve). The network acts as identifier of structural features on electrical loss process, so that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through experimental data taking into account core loss, c...