Forecasting the unit cost of a semiconductor product is an important task to the manufacturer. However, it is not easy to deal with the uncertainty in the unit cost. In order to effectively forecast the semiconductor unit cost, a collaborative and artificial intelligence approach is proposed in this study. In the proposed methodology, a group of domain experts is formed. These domain experts ar...

This paper presents modelling of internal combustion (IC) engine with adaptive neural networks. A radial basis function network model with both centres and weights adapted and a model with only weights adapted are compared with a fixed parameter model. The developed models are used in model based predictive control (MPC) to form an adaptive nonlinear MPC scheme and applied to engine speed track...

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...

In this paper, a novel hybrid Radial Basis Function Neural Network (RBF–NN) ensemble model is proposed for rainfall forecasting based on Kernel Partial Least Squares Regression (K–PLSR). In the process of ensemble modeling, the first stage the initial data set is divided into different training sets by used Bagging and Boosting technology. In the second stage, these training sets are input to t...

Image compression is a key technology in the development of various multi-media computer services and telecommunication applications such as video conferencing, interactive education and numerous other areas. Image compression techniques aim at removing (or minimizing) redundancy in data, yet maintains acceptable image reconstruction. In general the images used for compression are of different ...

The National Weather Service (NWS) Mesocyclone Detection Algorithms (MDA) use empirical rules to process velocity data from the Weather Surveillance Radar 1988 Doppler (WSR-88D). In this study Support Vector Machines (SVM) are applied to mesocyclone detection. Comparison with other classification methods like neural networks and radial basis function networks show that SVM are more effective in...

A method is described for using Radial Basis Function (RBF) neural networks to generate a certainty factor reliability measure along with the network's normal output. The certainty factor approach is then compared with another technique for measuring RBF reliability, Parzen windows. Both methods are implemented into RBF networks, and the results of using each approach are compared. Advantages a...

This paper investigates technique for solving spectrometry inverse problem the neural network as method for reconstruction of electron beam spectrum using depth-charge curve. The inverse problem turned into multivariable optimization and the form of spectrum is based on proposed three-parameter model. Radial basis function network calculates the parameters of this model. We developed computatio...

In this paper, we suggest a neural network signal detector using radial basis function (RBF) network. We employ this RBF Neural detector to detect the presence or absence of a known signal corrupted by different Gaussian, non-Gaussian and impulsive noise components. In case of non-Gaussian noise, experimental results show that RBF network signal detector has significant improvement in performan...

The paper presents the problem of using neural network for military vehicle classification on the basis of ground vibration. One of the main element of the system is a unit called geophone. This unit allows to measure amplitude of ground vibration in each direction for certain period of time. The value of amplitude is used to fix the characteristic frequencies of each vehicle. If we want to fix...