Preserving piece-wise linearity in fuzzy interpolation

Qiang Shen; Zhiheng Huang

doi:10.1109/FUZZY.2009.5277235

Preserving piece-wise linearity in fuzzy interpolation

Qiang Shen, Zhiheng Huang

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

11 Citations (Scopus)

192 Downloads (Pure)

Abstract

Fuzzy interpolative reasoning plays an important role in fuzzy modelling as it not only helps to reduce the number of rules in a rule base, but also provides an inference mechanism for sparse rule bases. In interpolation, it is desirable to preserve piece-wise linearity as piece-wise linear results can thus be inferred from piece-wise linear rules and observations. This safely ensures the ignorance of non-characteristic points in performing interpolations. However, almost all existing fuzzy interpolative reasoning methods do not preserve piecewise linearity for general polygonal fuzzy sets. This paper, based on the work of, proposes a new interpolative method which preserves this property.

Original language	English
Title of host publication	IEEE International Conference on Fuzzy Systems, 2009. FUZZ-IEEE 2009
Publisher	IEEE Press
Pages	575-580
Number of pages	6
ISBN (Electronic)	978-1-4244-3597-5
ISBN (Print)	978-1-4244-3596-8
DOIs	https://doi.org/10.1109/FUZZY.2009.5277235
Publication status	Published - Aug 2009
Event	Fuzzy Systems - Jeju Island, Korea (Republic of) Duration: 20 Aug 2009 → 24 Aug 2009 Conference number: 18

Conference

Conference	Fuzzy Systems
Abbreviated title	FUZZ-IEEE-2009
Country/Territory	Korea (Republic of)
City	Jeju Island
Period	20 Aug 2009 → 24 Aug 2009

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http://hdl.handle.net/2160/2911

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@inproceedings{12c9c0f19c094d339145c117a94018c1,

title = "Preserving piece-wise linearity in fuzzy interpolation",

abstract = "Fuzzy interpolative reasoning plays an important role in fuzzy modelling as it not only helps to reduce the number of rules in a rule base, but also provides an inference mechanism for sparse rule bases. In interpolation, it is desirable to preserve piece-wise linearity as piece-wise linear results can thus be inferred from piece-wise linear rules and observations. This safely ensures the ignorance of non-characteristic points in performing interpolations. However, almost all existing fuzzy interpolative reasoning methods do not preserve piecewise linearity for general polygonal fuzzy sets. This paper, based on the work of, proposes a new interpolative method which preserves this property.",

author = "Qiang Shen and Zhiheng Huang",

note = "Z. Huang and Q. Shen. Preserving Piece-wise Linearity in Fuzzy Interpolation. Proceedings of the 18th International Conference on Fuzzy Systems (FUZZ-IEEE'09), pp. 575-580, 2009.; Fuzzy Systems, FUZZ-IEEE-2009 ; Conference date: 20-08-2009 Through 24-08-2009",

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AB - Fuzzy interpolative reasoning plays an important role in fuzzy modelling as it not only helps to reduce the number of rules in a rule base, but also provides an inference mechanism for sparse rule bases. In interpolation, it is desirable to preserve piece-wise linearity as piece-wise linear results can thus be inferred from piece-wise linear rules and observations. This safely ensures the ignorance of non-characteristic points in performing interpolations. However, almost all existing fuzzy interpolative reasoning methods do not preserve piecewise linearity for general polygonal fuzzy sets. This paper, based on the work of, proposes a new interpolative method which preserves this property.

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DO - 10.1109/FUZZY.2009.5277235

M3 - Conference Proceeding (Non-Journal item)

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PB - IEEE Press

T2 - Fuzzy Systems

Y2 - 20 August 2009 through 24 August 2009

ER -

Preserving piece-wise linearity in fuzzy interpolation

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