In this paper, Radial Basis Function (RBF) method for interpolating two dimensional functions with localized features defined on irregular domain is presented. RBF points located inside the domain and on its boundary are chosen such that they are the image of conformally mapped points on concentric circles on a unit disk. On the disk, a fast RBF solver to compute RBF coefficients developed by K...

The morphology of Ganoderma lucidum BCCM 31549 mycelium in a repeated-batch fermentation (RBF) was studied for exopolysaccharide (EPS) production. RBF was optimised for time to replace and volume to replace. G. lucidum mycelium showed the ability to self-immobilise and exhibited high stability for repeated use in RBF with engulfed pellets. Furthermore, the ovoid and starburst-like pellet morpho...

Debris flow is one of the major threats for the sustainability of environmental and social development. The velocity directly determines the impact on the vulnerability. This study focuses on an approach using radial basis function (RBF) neural network and gravitational search algorithm (GSA) for predicting debris flow velocity. A total of 50 debris flow events were investigated in the Jiangjia...

Two difficulties are involved with traditional RBF networks: the initial configuration of an RBF network needs to be determined by a trial-and-error method, and the performance suffers degradation when the desired locations of the center of the RBF are not suitable. A novel RBF network is proposed to overcome these difficulties. A new radial basis function is used for hidden nodes, and the numb...

By visual inspection, both models produce good quality RBF images. However, comparison of regional averages to RBF values that were calculated from regional TACs (Figure C1), show that RBV must be included in the model (three-parameter model) if similar RBF estimates are required. RBF may be very sensitive to RBV, and if RBV is not fitted as the third parameter, or not corrected based on [O]CO ...

The performance of a Radial Basis Functions network (RBF) can be increased with the use of an ensemble of RBF networks because the RBF networks are successfully applied to solve classification problems and they can be trained by gradient descent algorithms. Reviewing the bibliography we can see that the performance of ensembles of Multilayer Feedforward (MF) networks can be improved by the use ...

This paper presents a new multiobjective evolutionary algorithm applied to a radial basis function (RBF) network design based on mult iobjective particle swarm optimization augmented with local search features. The algorithm is named the memetic multiobjective particle swarm optimization RBF network (MPSON) because it integrates the accuracy and structure of an RBF network. The proposed algorit...