NDLI: A novel method for new membership function calculation in HOSVD-based reduction to improve the operation needs

Content Provider	IEEE Xplore Digital Library
Author	Toth-Laufer, E. Rovid, A. Takacs, M. Rudas, I.J.
Copyright Year	2013
Description	Author affiliation: John von Neumann Fac. of Inf., Obuda Univ., Budapest, Hungary (Rovid, A.; Takacs, M.; Rudas, I.J.) \|\| Doctoral Sch. of Appl. Inf., Obuda Univ., Budapest, Hungary (Toth-Laufer, E.)
Abstract	Complexity reduction techniques should be used in those kinds of complex systems in which the evaluation time has a critical importance. Although the hierarchical clustered structure can reduce the number of the rules in contrast to the single-staged models, a further reduction technique is recommended to use in the subsystems to improve the evaluation time. A possible method among the several available ones is the widely used Higher Order Singular Value Decomposition (HOSVD), which is used to reduce the number of the rules in fuzzy logic-based systems. The authors studied this method and a novel pre-processing procedure was developed. This procedure can be used in HOSVD rule base reduction as an offline process to calculate the new membership function values belongs to crisp inputs. Due to offline processing the operation needs are reduced at all levels and all groups of the hierarchy where the reduction is performed separately. The novel method is based on the equidistant division of the input's domain, where the division is based on the accuracy of the input factor.
Starting Page	281
Ending Page	285
File Size	453034
Page Count	5
File Format	PDF
ISBN	9781479903030
e-ISBN	9781479903054
DOI	10.1109/SISY.2013.6662586
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-26
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Additives Accuracy Computational modeling Real-time systems Matrix decomposition Informatics Singular value decomposition
Content Type	Text
Resource Type	Article

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