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Knowledge Representation for Fuzzy Systems Based on Linguistic Variable Ontology and RDF

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Computer Science for Environmental Engineering and EcoInformatics (CSEEE 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 159))

Abstract

The Semantic Web is turning into a new generation web, where ontology is adopted as a standard for knowledge representation, and Resource Description Framework (RDF) is used to add structure and meaning to web applications. In order to incorporate fuzzy systems into the Semantic Web, this paper utilizes fuzzy ontology to represent formally the fuzzy linguistic variables, considering the semantic relationships between fuzzy concepts. Then fuzzy rule is described as a RDF resource with properties: IF and THEN, and rule’s antecedent and consequent is represented in RDF statement. Taking the fuzzy control system of industrial washing machine for example, the fuzzy system with ontology and RDF is built, which shows that this research enables distributed fuzzy applications on the Semantic Web.

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Author information

Authors and Affiliations

  1. Systems Engineering Institute, Dalian University of Technology, Dalian, 116024, China

    Hongyang Bao, Mudan Bai & Xiangpei Hu

  2. Transportation Management College, Dalian Maritime University, Dalian, 116026, China

    Jun Zhai

Authors
  1. Hongyang Bao
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  2. Jun Zhai
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  3. Mudan Bai
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  4. Xiangpei Hu
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Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Yuanxu Yu

  2. Kunming University of Science and Technology, Kunming, China

    Zhengtao Yu

  3. International Association for Scientific and High Technology, Kunming, China

    Jingying Zhao

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© 2011 Springer-Verlag Berlin Heidelberg

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Bao, H., Zhai, J., Bai, M., Hu, X. (2011). Knowledge Representation for Fuzzy Systems Based on Linguistic Variable Ontology and RDF. In: Yu, Y., Yu, Z., Zhao, J. (eds) Computer Science for Environmental Engineering and EcoInformatics. CSEEE 2011. Communications in Computer and Information Science, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22691-5_69

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  • DOI: https://doi.org/10.1007/978-3-642-22691-5_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22690-8

  • Online ISBN: 978-3-642-22691-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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