SUMMARY Representing the concept of numerical data by linguistic rules is often desir­ able. In this paper, we present a novel rule-extraction algorithm from the radial basis function (RBF) neural network classifier for representing the hidden concept of numerical data. Gaussian function is used as the basis function of the RBF network. When training the RBF neural network, we allow for large o...

According to literature, it is well-known that the training algorithm of RBF neural networks depends a lot by the specific way to obtain the positioning of RBF centers over the input data space, and to fit the neural weights to the output layer, respectively. Having as starting point a real pattern recognition task belonging to video imagery to solve, this paper presents a comparative analysis ...

Personal credit evaluation is the basic method for the commercial banks to avoid the consumer credit risk. On one hand, the credit behavior of individuals is complex; on the other hand the personal credit assessment system in our country is not sound, assessment methods are mostly objective, therefore, more and better scientific methods for credit risk assessment need to be introduced. This pap...

the electronic industry suffers a rapid changing and highly rival environment. thus, firms have an essential need to strive for acquiring the competitive advantage. strategy organizational agility (soa) is a tool which enables to assist firms to attain the competitive advantage. therefore, this study benchmarks the core competencies from a case study within the supply chain network and establis...

This paper works on hybrid force/position control in robotic manipulation and proposes an improved radial basis functional RBF neural network, which is a robust relying on the Hamilton Jacobi Issacs principle of the force control loop. The method compensates uncertainties in a robot system by using the property of RBF neural network. The error approximation of neural network is regarded as an e...

A neural network-based model reference adaptive control approach (MRAC) for ship steering systems is proposed in this paper. For the nonlinearities of ship steering system, performances of traditional adaptive control algorithms are not satisfactory in fact. The presented MRAC system utilizes RBF neural network to approximate the unknown nonlinearities in order to get a high adaptive control pe...

The estimation of crop chlorophyll content could provide technical support for precision agriculture. Canopy spectral reflectance was simulated for different chlorophyll levels using radiative transfer models. Then with multiperiod measured hyperspectral data and corresponding chlorophyll content, after extracting six wavelet energy coefficients from the responded bands, an evaluation of soybea...

Because simulation turntable servo system is highly nonlinear and uncertainty plants, a fuzzy neural network PID controller is proposed based on the Radial Basis Function (RBF). Up to now, various kinds of nonlinear PID controllers have been designed in order to satisfactorily control this system and some of them applied in actual systems with different degrees. Given this background, the step ...

In this paper, we propose a hybrid approach for mammographic images interpretation in order to detect the benign and malignant anomalies. Using a neural evolutionary approach based on the Radial Basis Function neural network (RBF) and the evolutionary strategy (ES). After applying the growing region algorithm in segmentation stage, the RBF neural network detects the suspect regions. The inferen...