Proximate composition, pH and amylose content of ripe Cavendish banana flour (RBF) prepared in this study were compared with all-purpose wheat flour (WF). RBF was found to be significantly (P < 0.05) higher in total carbohydrates and minerals content, while significantly (P < 0.05) lower in protein and fat contents compared with those of WF. Wheat-ripe banana composite flours (W-RBF) prepared b...

Meshless solution to differential equations using radial basis functions (RBF) is an alternative grid based methods commonly used. Since the meshless method does not need underlying connectivity in form of control volumes or elements, issues such as skewness that adversely impact accuracy are eliminated. Gaussian, Multiquadrics and inverse some most popular RBFs used for solutions fluid flow he...

In this paper, a new localized radial basis function (RBF) method based on partition of unity (PU) is proposed for solving boundary and initial-boundary value problems. The benefits from direct discretization approach called the “direct RBF (D-RBF-PU)” method. Thanks to avoiding all derivatives PU weight functions as well lower local approximants, faster simpler than standard RBF-PU Besides, di...

In this paper, learning algorithms for radial basis function (RBF) networks are discussed. Whereas multilayer perceptrons (MLP) are typically trained with backpropagation algorithms, starting the training procedure with a random initialization of the MLP's parameters, an RBF network may be trained in many different ways. We categorize these RBF training methods into one-, two-, and three-phase ...

The application of the current new generation communication technology is gradually diversified, and global Internet users are increasing, leading some large enterprises to increasingly rely on faster more efficient big data processing technology. In order solve shortcomings algorithms, such as slow computing speed, accuracy be improved, poor online real-time learning ability, this research com...

We present a generalization of the RBF-FD method that allows full control of the overlap between RBF-FD stencils. We accomplish this by introducing a continuous overlap parameter δ ∈ [0, 1] such that δ = 1 recovers the standard RBF-FD method and δ = 0 results in a full decoupling of the RBF-FD stencils. We show with a simple example that global interpolation with both RBFs and RBFs augmented wi...

The current fault diagnosis methods based on conventional BP neural network and RBF neural network exist long training time, slow convergence speed and low judgment accuracy rate and so on. In order to improve the ability of fault diagnosis, this paper puts forward a kind of fault diagnosis method based on RBF Neural Network improved by PSO algorithm. By using particle swarm algorithm’s heurist...

We present a generalization of the RBF-FD method that allows full control of the overlap between RBF-FD stencils. We accomplish this by introducing a continuous overlap parameter δ ∈ [0, 1] such that δ = 1 recovers the standard RBF-FD method and δ = 0 results in a full decoupling of the RBF-FD stencils. We show with a simple example that global interpolation with both RBFs and RBFs augmented wi...

In this paper we propose an improvement for a semi-supervised learning algorithm based on Gaussian random fields and harmonic functions. Semi-supervised functions is graph-based method that uses data point similarity to connect unlabeled points with labeled points, thus achieving label propagation. The proposed concerns the way of determining between two by using hybrid RBF-kNN kernel. This mak...

This paper proposes an adaptive evolutionary radial basis function (RBF) network algorithm to evolve accuracy and connections (centers and weights) of RBF networks simultaneously. The problem of hybrid learning of RBF network is discussed with the multi-objective optimization methods to improve classification accuracy for medical disease diagnosis. In this paper, we introduce a time variant mul...