Growth analysis of neighbor network for evaluation of damage progress

Ken Ichi Fukui, Kazuhisa Sato, Junichiro Mizusaki, Kazumi Saito, Masahiro Kimura, Masayuki Numao

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

2 Citations (Scopus)

Abstract

We constructed two types of neighbor networks, i.e., TOP k and k-MNN (Mutually Nearest Neighbor) networks, on observed AE (Acoustic Emission) data produced by damages in SOFC (Solid Oxide Fuel Cell). Afterwards, we analyzed growth properties of the neighbor networks for evaluation of damage progress. The results show that the power index of degree dynamically changes as damage progress phase changes. Also we found the decrease of cluster coefficient and shrinking effective diameter in k-MNN network reflect the occurrence of various combination of damages.

Original languageEnglish
Title of host publication13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009
Pages933-940
Number of pages8
DOIs
Publication statusPublished - 2009
Event13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009 - Bangkok, Thailand
Duration: 2009 Apr 272009 Apr 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5476 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009
CountryThailand
CityBangkok
Period09/4/2709/4/30

Keywords

  • Cluster coefficient
  • Complex network
  • Degree
  • Effective diameter
  • Temporal analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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