This paper employs ANN (Artificial Neural Network) models to estimate GHI (global horizontal irradiance) for three major cities in the UAE (United Arab Emirates), namely Abu Dhabi, Dubai and Al-Ain. City data are then used to develop a comprehensive global GHI model for other nearby locations in...

The coastal areas of Japan were hard hit by a magnitude 9.0 earthquake on 11 March 2011. The earthquake triggered a disastrous tsunami over the area which led to massive destruction. In this paper, tsunami-induced changes in Soma, Watari, Natori and Iwanuma areas using Landsat 7 ETM+ and EO-1...

Short-term wind speed forecasting is of great importance for wind farm operations and the integration of wind energy into the power grid system. Adaptive and reliable methods and techniques of wind speed forecasts are urgently needed in view of the stochastic nature of wind resource varying from...

In this paper we investigate, the possibility of using an adaptive Artificial Neural Network (ANN), in order to find a suitable model for sizing Stand-Alone Photovoltaic (SAPV) systems, based on a minimum of input data. The model combines Radial Basis Function (RBF) network and Infinite Impulse...

This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH)....

Pathological processes cause abnormal regional motions of the heart. Regional wall motion analyses are important to evaluate the success of therapy, especially of cell therapy, since the recovery of the heart in cell therapy proceeds slowly and results in only small changes of ventricular wall...

An increasingly popular and promising approach to solve option pricing models is the use of numerical methods based on radial basis functions (RBF). These techniques yield high levels of accuracy, but have the drawback of requiring the inversion of large full system matrices. In the present...

In this paper, the problem of the interpolation of explicit surfaces with vertical faults from scattered data is studied. A new interpolation scheme for compactly supported radial basis functions is proposed which is well adapted to our purpose. This method is based on the construction of an...

Various artificial neural networks types are examined and compared for the prediction of surface roughness in manufacturing technology. The aim of the study is to evaluate different kinds of neural networks and observe their performance and applicability on the same problem. More specifically,...

A method for the selection of centers for radial basis function (RBF) approximation is introduced, which reduces the computational cost of the evaluation of the approximating function. The method takes into consideration:1.the geometric information (arc length and curvature) of the approximating...