Optimal cooperation between external criterion and data division in GMDH

Authors:
C. -Z. He;J. Wu;J. -A. Müller
Affiliations:
Business School of Sichuan University, Chengdu, P.R.China 610064;Business School of Sichuan University, Chengdu, P.R.China 610064;Hochschule für Technik und Wirtschaft, Germany
Venue:
International Journal of Systems Science
Year:
2008

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Abstract

The problem of cooperation between external criterion and data division is important for application and development of group method of data handling (GMDH) theory. Based on research of 'critical noise level' and 'noise immunity', this article presents the concept of 'expected critical noise level'. The relationship between 'expected critical noise level' and both prediction set and model structure is expressed by a formula. According to 'expected critical noise level', a selection method is designed, which is able to obtain an optimal cooperation between external criterion and data division in GMDH. Finally, the corresponding algorithm and an example are given.