Modifying Explicit Finite Difference Method by Using Radial Basis Function Neural Network

Fast Voltage and Power Flow Contingency Ranking Using Enhanced Radial Basis Function Neural Network

Deregulation of power system in recent years has changed static security assessment to the major concerns for which fast and accurate evaluation methodology is needed. Contingencies related to voltage violations and power line overloading have been responsible for power system collapse. This paper presents an enhanced radial basis function neural network (RBFNN) approach for on-line ranking of ...

Training Radial Basis Function Neural Network using Stochastic Fractal Search Algorithm to Classify Sonar Dataset

Radial Basis Function Neural Networks (RBF NNs) are one of the most applicable NNs in the classification of real targets. Despite the use of recursive methods and gradient descent for training RBF NNs, classification improper accuracy, failing to local minimum and low-convergence speed are defects of this type of network. In order to overcome these defects, heuristic and meta-heuristic algorith...

Improving Accuracy of DGPS Correction Prediction in Position Domain using Radial Basis Function Neural Network Trained by PSO Algorithm

Differential Global Positioning System (DGPS) provides differential corrections for a GPS receiver in order to improve the navigation solution accuracy. DGPS position signals are accurate, but very slow updates. Improving DGPS corrections prediction accuracy has received considerable attention in past decades. In this research work, the Neural Network (NN) based on the Gaussian Radial Basis Fun...

Long-Term Peak Demand Forecasting by Using Radial Basis Function Neural Networks

Prediction of peak loads in Iran up to year 2011 is discussed using the Radial Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the current and future trends is carried out for global grid of Iran. Predictions were done for target years 2007 to 2011 respectively. Unlike short-term load forecasting, long-term load forecasting is mainly affected by economy...

A supervised radial basis function neural network