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The application of a fuzzy‐rule‐based system in an exposition of the antecedents of sedge warbler song flight
Author(s) -
Bey Malcolm J.,
Buchanan Katherine L.,
Tang YuCheng
Publication year - 2004
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.2004.00258.x
Subject(s) - computer science , fuzzy logic , construct (python library) , fuzzy rule , interpretation (philosophy) , set (abstract data type) , exposition (narrative) , artificial intelligence , decision tree , decision rule , fuzzy set , duration (music) , data mining , machine learning , art , literature , programming language
The utilization of a fuzzy aspect within data analysis attempts to move from a quantitative to a more qualitative investigative environment. As such, this may allow the more non‐quantitative researchers results they can use, based on sets of linguistic terms. In this paper an inductive fuzzy decision tree approach is utilized to construct a fuzzy‐rule‐based system for the first time in a biological setting. The specific biological problem considered attempts to identify the antecedents (conditions in the fuzzy decision rules) which characterize the length of song flight of the male sedge warbler when attempting to attract a mate. Hence, for a non‐quantitative investigator the resultant set of fuzzy rules allows an insight into the linguistic interpretation on the relationship between associated characteristics and the respective song flight duration.