Fuzzy rule interpolation based fuzzy signature structure in building condition evaluation

Gergely I. Molnárka, Szilveszter Kovács, L. Kóczy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The complexity of the residential house structures makes their condition evaluation difficult. Taking the human experts' thinking into consideration the linguistic approach seems reasonable, therefore the fuzzy set theory may provide a basis for creating an expert system. In practice, the assessment of some predefined attributes of building components may give a comprehensive value about the condition of the examined building on a relative scale. The data structure of building evaluation procedure makes clear that the fuzzy signature structure is helpful in analysis. The numerous building components that determine the character of the given building can turn to an unnecessarily large rule-base. The fuzzy rule interpolation and the corresponding sparse fuzzy rule-based knowledge representation could be a reasonably efficient structure for handling the building evaluation procedure. In this paper the fuzzy rule interpolation as a novel aggregation method in fuzzy signature structures is proposed. Its application is presented with a case study of roof structure evaluation of a classic urban-type residential house located in a historic district of Budapest, Hungary.

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2214-2221
Number of pages8
ISBN (Print)9781479920723
DOIs
Publication statusPublished - Sep 4 2014
Event2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 - Beijing, China
Duration: Jul 6 2014Jul 11 2014

Other

Other2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014
CountryChina
CityBeijing
Period7/6/147/11/14

Fingerprint

Fuzzy rules
Fuzzy Rules
Interpolation
Signature
Interpolate
Evaluation
Fuzzy set theory
Knowledge representation
Linguistics
Roofs
Expert systems
Data structures
Agglomeration
Rule Base
Fuzzy Set Theory
Knowledge Representation
Expert System
Aggregation
Data Structures
Attribute

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Applied Mathematics
  • Theoretical Computer Science

Cite this

Molnárka, G. I., Kovács, S., & Kóczy, L. (2014). Fuzzy rule interpolation based fuzzy signature structure in building condition evaluation. In Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE (pp. 2214-2221). [6891883] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2014.6891883

Fuzzy rule interpolation based fuzzy signature structure in building condition evaluation. / Molnárka, Gergely I.; Kovács, Szilveszter; Kóczy, L.

Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2214-2221 6891883.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Molnárka, GI, Kovács, S & Kóczy, L 2014, Fuzzy rule interpolation based fuzzy signature structure in building condition evaluation. in Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE., 6891883, Institute of Electrical and Electronics Engineers Inc., pp. 2214-2221, 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014, Beijing, China, 7/6/14. https://doi.org/10.1109/FUZZ-IEEE.2014.6891883
Molnárka GI, Kovács S, Kóczy L. Fuzzy rule interpolation based fuzzy signature structure in building condition evaluation. In Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2214-2221. 6891883 https://doi.org/10.1109/FUZZ-IEEE.2014.6891883
Molnárka, Gergely I. ; Kovács, Szilveszter ; Kóczy, L. / Fuzzy rule interpolation based fuzzy signature structure in building condition evaluation. Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 2214-2221
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