On the Applicability of the NetFAN-Approach to Function Approximation

Olaf Huwendiek, Werner Brockmann

Abstract

Fuzzy systems were shown to be universal approximators, so are their trainable variant, the neuro-fuzzy systems. But fuzzy systems suffer from the curse of dimensionality, i.e. a very strong increase in computational and memory demands with an increasing number of input variables. This paper describes the NetFAN-approach to reduce this drawback by decomposition. It also proofs that such decomposed systems are universal approximators. The benchmark example of modeling the energy and water consumption of a building not only demonstrates that it achieves approximation capabilities like artificial neural networks. It also gives a notion how to utilize abstract background knowledge.

Original languageEnglish
Pages477-482
Number of pages6
DOIs
Publication statusPublished - 01.01.1997
EventProceedings of the 1997 6th IEEE International Conference on Fussy Systems
- Barcelona, Spain
Duration: 01.07.199705.07.1997
Conference number: 47111

Conference

ConferenceProceedings of the 1997 6th IEEE International Conference on Fussy Systems
Abbreviated titleFUZZ-IEEE'97
Country/TerritorySpain
CityBarcelona
Period01.07.9705.07.97

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