In recent decades, hybridization of superior attributes few algorithms was proposed to aid in covering more areas complex application as well improves performance. Condition monitoring is a major component predictive maintenance which monitors the condition and identifies significant changes machinery parameter perform early detection prevent equipment defects that could cause unplanned downtim...

Classification has been a major problem of study whose application includes speaker recognition, character recognition, etc. In this paper we first adapt the Radial Basis Function Network (RBFN) for classification problems and then use customized Evolutionary Algorithms to evolve the RBFN. The neurons of the RBFN correspond to some class out of the available output classes. Linear addition of o...

In this paper, a face recognition algorithm using multi feature and Radial basis Function Network (RBFN) is proposed. The algorithm consists of three steps. In the first step, a coarse classification is performed using Fourier frequency spectrum feature, and only the first k gallery images with minimum Euclidean distance to the probe image are retained. In the second step, the Principal Compone...

Face detection from cluttered images is very challenging due to the wide variety of faces and the complexity of image backgrounds. In this paper, we propose a neural network based approach for locating frontal views of human faces in cluttered images. We use a radial basis function network (RBFN) for separation of face and non-face patterns, and the complexity of RBFN is reduced by principal co...

The voltage stability constrained Available Transfer Capability (ATC) computations are obtained on IEEE 9-bus by running load flow until the voltage collapse point is achieved by enhancing the load in steps with constant power factor. These results are used to train the Neural Network by using Radial Basis Function Neural Network (RBFN) technique. The comparative results of convergence method, ...

Biofiltration is emerging as a promising cost effective technique for the Volatile Organic Compounds (VOCs) removal from industrial waste gases. In the present investigation a comparative modeling study has been carried out using Radial Basis Function Neural Network (RBFN) and Response Surface Methodology (RSM) to predict and optimize the performance of a biofilter system treating toluene (a mo...

This paper describes a robust and efficient method for rotation and location independent identification and localization of facial images using one modified Radial Basis Function Network (RBFN) which embeds a new Heuristic Based Clustering (HBC) and Back Propagation (BP) learning. HBC in RBFN determines the natural number of clusters or groups on the basis of 'person-view'. BP network...

Face detection from cluttered images is very challenging due to the diverse variation of face appearance and the complexity of image background. In this paper, we propose a neural network based approach for locating frontal views of human faces in cluttered images. We use a radial basis function network (RBFN) for separation of face and non-face patterns and the complexity of RBFN is reduced by...

-This paper presents a financial distress prediction model that combines the approaches of neural network learning and logit analysis. This combination can retain the advantages and avoid the disadvantages of the two kinds of approaches in solving such a problem. The radial basis function network (RBFN) is adopted to construct the prediction model. The architecture of RBFN allows the grouping o...

In this paper, an approach to generate surrogate models constructed by radial basis function networks (RBFN) with a priori bias is presented. RBFN as a weighted combination of radial basis functions only, might become singular and no interpolation is found. The standard approach to avoid this is to add a polynomial bias, where the bias is defined by imposing orthogonality conditions between the...