A Prediction Model Using Parallel Kernel RBF Neural Networks
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Abstract:
Radial Basis Function Neural Networks(RBF NN) are frequently used for regression prediction.But kernel matrix computation for high dimensional data source demands heavy computing power.To shorten computing time,the paper designs a parallel algorithm to compute the kernel function matrix of RBF NN and applies it to the prediction of converter re-vanadium modeling.The paper then implements the algorithm on a cluster of computing workstations using MPI.Finally,experiment is done with the practical data to study the speedups and accuracy of the algorithm.
