The mind in the model - Modelling expert knowledge with fuzzy sets

Judith Janssen; Dionysius C.M. Augustijn; Ralph Mathias Johannes Schielen; A.G. van Os

The mind in the model - Modelling expert knowledge with fuzzy sets

Judith Janssen, Dionysius C.M. Augustijn (Editor), Ralph Mathias Johannes Schielen, A.G. van Os (Editor)

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Abstract

Fuzzy logic offers a way of capturing qualitative knowledge in models. We tested its application in modelling for long term river management planning. We used fuzzy logic to model landscape impacts of different river measures. Preliminary results show that the method allows for modelling expert knowledge concerning landscape effects. The resulting model is rapid and transparent. However, the elicitation of the -often ambiguous- expert knowledge remains one of the major concerns.

Original language	Undefined
Pages	14-14
Publication status	Published - 2 Nov 2006
Event	NCR-days 2006 - Enschede, Netherlands Duration: 2 Nov 2006 → 3 Nov 2006

Conference

Conference	NCR-days 2006
Country/Territory	Netherlands
City	Enschede
Period	2/11/06 → 3/11/06

Keywords

METIS-233973
IR-67877

Access to Document

Janssen06mind

Cite this

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title = "The mind in the model - Modelling expert knowledge with fuzzy sets",

abstract = "Fuzzy logic offers a way of capturing qualitative knowledge in models. We tested its application in modelling for long term river management planning. We used fuzzy logic to model landscape impacts of different river measures. Preliminary results show that the method allows for modelling expert knowledge concerning landscape effects. The resulting model is rapid and transparent. However, the elicitation of the -often ambiguous- expert knowledge remains one of the major concerns.",

keywords = "METIS-233973, IR-67877",

author = "Judith Janssen and Augustijn, {Dionysius C.M.} and Schielen, {Ralph Mathias Johannes} and {van Os}, A.G.",

year = "2006",

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AU - Schielen, Ralph Mathias Johannes

A2 - Augustijn, Dionysius C.M.

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N2 - Fuzzy logic offers a way of capturing qualitative knowledge in models. We tested its application in modelling for long term river management planning. We used fuzzy logic to model landscape impacts of different river measures. Preliminary results show that the method allows for modelling expert knowledge concerning landscape effects. The resulting model is rapid and transparent. However, the elicitation of the -often ambiguous- expert knowledge remains one of the major concerns.

AB - Fuzzy logic offers a way of capturing qualitative knowledge in models. We tested its application in modelling for long term river management planning. We used fuzzy logic to model landscape impacts of different river measures. Preliminary results show that the method allows for modelling expert knowledge concerning landscape effects. The resulting model is rapid and transparent. However, the elicitation of the -often ambiguous- expert knowledge remains one of the major concerns.

KW - METIS-233973

KW - IR-67877

M3 - Paper

SP - 14

EP - 14

T2 - NCR-days 2006

Y2 - 2 November 2006 through 3 November 2006

ER -