Fuzzy Interpolation and Extrapolation: A Practical Approach


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dc.contributor.author Huang, Zhiheng
dc.contributor.author Shen, Qiang
dc.date.accessioned 2008-02-27T16:11:02Z
dc.date.available 2008-02-27T16:11:02Z
dc.date.issued 2008-02-26
dc.identifier.citation Huang , Z & Shen , Q 2008 , ' Fuzzy Interpolation and Extrapolation: A Practical Approach ' IEEE Transactions on Fuzzy Systems , vol 16 , no. 1 , pp. 13-28 . , 10.1109/TFUZZ.2007.902038 en
dc.identifier.issn 1063-6706
dc.identifier.other PURE: 75658
dc.identifier.other dspace: 2160/514
dc.identifier.uri http://hdl.handle.net/2160/514
dc.identifier.uri http://ieeexplore.ieee.org/Xplore/login.jsp?url=/iel5/91/4358784/04358815.pdf?arnumber=4358815 en
dc.description Z. Huang and Q. Shen. Fuzzy interpolative and extrapolative reasoning: a practical approach. IEEE Transactions on Fuzzy Systems, 16(1):13-28, 2008. en
dc.description.abstract Fuzzy interpolation does not only help to reduce the complexity of fuzzy models, but also makes inference in sparse rule-based systems possible. It has been successfully applied to systems control, but limited work exists for its applications to tasks like prediction and classification. Almost all fuzzy interpolation techniques in the literature make strong assumptions that there are two closest adjacent rules available to the observation, and that such rules must flank the observation for each attribute. Also, some interpolation approaches cannot handle fuzzy sets whose membership functions involve vertical slopes. To avoid such limitations and develop a more practical approach, this paper extends the work of Huang and Shen. The result enables both interpolation and extrapolation which involve multiple fuzzy rules, with each rule consisting of multiple antecedents. Two realistic applications, namely truck backer-upper control and computer activity prediction, are provided in this paper to demonstrate the utility of the extended approach. Experiment-based comparisons to the most commonly used Mamdani fuzzy reasoning mechanism, and to other existing fuzzy interpolation techniques are given to show the significance and potential of this research. en
dc.format.extent 16 en
dc.language.iso eng
dc.relation.ispartof IEEE Transactions on Fuzzy Systems en
dc.title Fuzzy Interpolation and Extrapolation: A Practical Approach en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1109/TFUZZ.2007.902038
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Peer reviewed en

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