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

conference contribution
posted on 2023-05-23, 04:15 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 title

Proceedings The 5th International Conference on Information Technology and Applications

Editors

Liang, YC

Pagination

683-686

ISBN

978-0-9803267-2-7

Department/School

School of Information and Communication Technology

Publisher

iCITA

Place of publication

Carins, Qld

Event title

International Conference on Information Technology and Applications: iCITA

Event Venue

Carins, Qld

Date of Event (Start Date)

2008-06-23

Date of Event (End Date)

2008-06-26

Rights statement

Copyright 2008 ICITA

Repository Status

  • Restricted

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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