University of Tasmania
Browse
02-au-xu.pdf (488.33 kB)

A novel approach for determining the optimal number of hidden layer neurons for FNN's and its application in data mining

Download (488.33 kB)
conference contribution
posted on 2023-05-26, 09:19 authored by Shuxiang XuShuxiang Xu, Chen, L
Optimizing the number of hidden layer neurons for an FNN (feedforward neural network) to solve a practical problem remains one of the unsolved tasks in this research area. In this paper we review several mechanisms in the neural networks literature which have been used for determining an optimal number of hidden layer neuron (given an application), propose our new approach based on some mathematical evidence, and apply it in financial data mining. Compared with the existing methods, our new approach is proven (with mathematical justification), and can be easily handled by users from all application fields.

History

Publication status

  • Published

Event title

5th International Conference on Information Technology and Applications (ICITA 2008)

Event Venue

Cairns, Queensland, Australia

Date of Event (Start Date)

2008-06-23

Date of Event (End Date)

2008-06-26

Repository Status

  • Open

Usage metrics

    University Of Tasmania

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC