What is it about?
Utilizing Bayesian predictor in choosing the "best" single neural network in each sample time for combination multiple neural networks.
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Why is it important?
Long range prediction normally will accumulate an error in each sample time, therefore by having Bayesian combination predictor in selective combination in multiple neural networks did improved the performance of the network.
Perspectives
One of my early article during my PhD with my supervisor Dr Jie Zhang
Dr Zainal Ahmad
Universiti Sains Malaysia
Read the Original
This page is a summary of: Bayesian selective combination of multiple neural networks for improving long-range predictions in nonlinear process modelling, Neural Computing and Applications, November 2004, Springer Science + Business Media,
DOI: 10.1007/s00521-004-0451-y.
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