This paper presents a new two-layer recurrent neural network (RNN) for a power system stabilizer (PSS) design called the recurrent neural network power system stabilizer (RNNPSS). The RNNPSS consists of a recurrent neural network identifier (RNNI) that tracks and identifies the power generator and a recurrent neural network controller (RNNC) that supplies an adaptive signal to the governor and ...

This paper presents the application of three main Artificial Neural Networks (ANNs) in damage detection of steel bridges. This method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. The changes in structural response is used to identify the states of structural damage. To circumvent the difficulty arising from the non-linear n...

In this paper, a state-of-the-art neuron mathematical model of neural tensor network (NTN) is proposed to RDF knowledge base completion problem. One of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. For this reason, a new representation of this network is suggested that solves this difficulty. In the representation, th...

this paper investigates the residual stress fields in the vicinity of weld bead in hsla-65 steel weldments using a neural network. this study consists of two cases: (i) the experimental analysis was carried out the measurements of residual stresses by xrd technique. many different specimens that were subjected to different conditions were studied. the values and distributions of residual stress...

Modelling is carried out to map the relationship between the input process parameters and the output response, considered in the machining process. To represent real-world systems of considerable complexity, an artificial neural network (ANN) model is often utilized to replace the mathematical approximation of the relationship. This paper explains the methodological procedure and the outcome of...

in recent decades artificial neural networks (anns) have shown great ability in modeling and forecasting non-linear and non-stationary time series and in most of the cases especially in prediction of phenomena have showed very good performance. this paper presents the application of artificial neural networks to predict drought in yazd meteorological station. in this research, different archite...

Several neural network architectures have been developed over the past several years. One of the most popular and most powerful architectures is the multilayer perceptron. This architecture will be described in detail and recent advances in training of the multilayer perceptron will be presented. Multilayer perceptrons are trained using various techniques. For years the most used training metho...