A precise short-term load forecasting technique is required for the economic and reliable operation of power system. Modern load forecasting techniques especially ANN methods are attractive as they have the ability to handle the non-linear relationships between load, weather temperature and the factors affecting it directly. In this paper, an investigation on the use of ANN for short term load ...

From a geometric perspective most nonlinear binary classification algorithms, including state of the art versions of Support Vector Machine (SVM) and Radial Basis Function Network (RBFN) classifiers, and are based on the idea of reconstructing indicator functions. We propose instead to use reconstruction of the signed distance function (SDF) as a basis for binary classification. We discuss prop...

The present paper discusses the stability analysis of discrete-time uncertain nonlinear systems with time-varying delay, uncertainties related to parametric uncertainty and unknown nonlinearity. The time-varying delay considered has minimum and maximum bounds. The novelty of Chebyshev Neural Network (CNN) is that it requires much less computation time as compared to multi layer neural network (...

Introduction: The capability of receivers employing multiple antennas to increase the achievable system capacity and to suppress the effects of co-channel interference has motivated intense research in the field of space-time equalisation [1]. Most contributions, however, focus on sub-optimal linear receivers or investigate the performance of maximum-likelihood sequence estimators (MLSE), which...

The two most widely used neural models, multilayer perceptron (MLP) and radial basis function network (RBFN), are presented in the framework of system identification and control. The main steps for building such nonlinear black box models are regressor choice, selection of internal architecture, and parameter estimation. The advantages of neural network models are summarized: universal approxim...

In recent years, voltage limit violation and power system load-generation imbalance, i.e., line loading limit violation have been responsible for several incidents of major network collapses leading to partial or even complete blackouts. Alleviation of line overloads is the suitable corrective action in this regard. The control action strategies to limit the line loading to the security limits ...

Seven different Radial Basis Functions have been applied in a Feedforward Neural Network and tested on five different real or simulated multivariate modelling problems. A short theory of Radial Basis Functions is presented as well as the particular implementation of the Radial Basis Function Network (RBFN). The real world data modelling problems are; identifying the dynamic actuator characteris...