A hybrid simultaneous perturbation artificial bee colony and back-propagation algorithm for training a local linear radial basis neural network on ore grade estimation

In this paper, a local linear radial basis function (LLRBF) neural network that uses a skewed Gaussian activation function, called LLRBF-SG, is applied to the problem of ore grade estimation of highly skewed data from the Esfordi phosphate deposit. The network is trained using SPABC-BP, a method tha...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 235; pp. 217 - 227
Main Authors:	Jafrasteh, Bahram, Fathianpour, Nader
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 26.04.2017
Subjects:	Highly skewed data Local linear radial basis function Ore grade estimation Simultaneous perturbation artificial bee colony algorithm Skewed Gaussian activation function Highly skewed data Local linear radial basis function Ore grade estimation Simultaneous perturbation artificial bee colony algorithm Skewed Gaussian activation function
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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