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Authors: Yeong-Hyeon Byeon and Keun-Chang Kwak

Affiliation: Chosun University, Korea, Republic of

Keyword(s): Knowledge Discovery, Linguistic Modelling, Conditional Fuzzy Clustering, Interval Type-2 Fuzzy.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Clustering and Classification Methods ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: This paper is concerned with a method for designing improved Linguistic Model (LM) using Conditional Fuzzy Clustering(CFC) with two different Interval Type-2 (IT2) fuzzy approaches. The fuzzification factor and contexts with IT2 fuzzy approach are used to deal with uncertainty of clustering,. This proposed clustering technique has characteristics that estimate the prototypes by preserving the homogeneity between the clustered patterns from the IT2-based contexts, and controls the amount of fuzziness of fuzzy c-partition. Thus, the proposed method can represent a nonlinear and complex characteristic more effectively than conventional LM. The experimental partial results on coagulant dosing process in a water purification plant revealed that the proposed method showed a better performance in comparison to the previous works.

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Paper citation in several formats:
Byeon, Y. and Kwak, K. (2015). Knowledge Discovery and Modeling based on Conditional Fuzzy Clustering with Interval Type-2 Fuzzy. In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR; ISBN 978-989-758-158-8; ISSN 2184-3228, SciTePress, pages 440-444. DOI: 10.5220/0005617804400444

@conference{kdir15,
author={Yeong{-}Hyeon Byeon and Keun{-}Chang Kwak},
title={Knowledge Discovery and Modeling based on Conditional Fuzzy Clustering with Interval Type-2 Fuzzy},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR},
year={2015},
pages={440-444},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005617804400444},
isbn={978-989-758-158-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - KDIR
TI - Knowledge Discovery and Modeling based on Conditional Fuzzy Clustering with Interval Type-2 Fuzzy
SN - 978-989-758-158-8
IS - 2184-3228
AU - Byeon, Y.
AU - Kwak, K.
PY - 2015
SP - 440
EP - 444
DO - 10.5220/0005617804400444
PB - SciTePress

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