Bayesian selective combination of multiple neural networks for improving long-range predictions in nonlinear process modelling

Zainal Ahmad, Jie Zhang
  • Neural Computing and Applications, November 2004, Springer Science + Business Media
  • DOI: 10.1007/s00521-004-0451-y

Selective combination using Bayes Rule in multiple neural networks combination

What is it about?

Utilizing Bayesian predictor in choosing the "best" single neural network in each sample time for combination multiple neural networks.

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

Dr Zainal Ahmad
Universiti Sains Malaysia

One of my early article during my PhD with my supervisor Dr Jie Zhang

Read Publication

http://dx.doi.org/10.1007/s00521-004-0451-y

The following have contributed to this page: Dr Zainal Ahmad

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