The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
권호 표지

A clustering method using the Coulomb Energy Network

쿨롱네트워크를 이용한 집락분석

  • 이석훈 ((305-764) 대전시 유성구 궁동 220, 충남대학교 통계학과) ;
  • 박래현 ((305-764) 대전시 유성구 궁동 220, 충남대학교 통계학과) ;
  • 김응환 ((301-130) 대전시 중구 문화동, 충남기계공업고등학교)
  • Published : 1995.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

This article deals with the problem that all the statistical clustering methods do not supply the clustering rule after the analysis. We modify the Coulomb Energy Network model basically developed in physics and suggest one model appropriate for our purpose and show the implementation using an actual data. Finally the method suggested is compared with one of the well known methods, K-means algorithm using Rand C.

기존의 집락분석은 집락화만을 목적으로 하기 때문에 분석이 끝나면 집락분석에 사용된 규칙을 보존하지 못하는 문제를 갖고 있다. 이러한 문제를 인간의 뇌의 성질을 연구하는 신경회로망 분야에서 사용하는 모형중 하나인 쿨롱 에너지 네트워크 모형을 변형 발전시켜서 해결하여 보았다. 이 모형을 이용한 분석의 실제 예를 보이고 기존의 기법들과의 비교를 통하여 거의 유사한 집락형성을 보여주고 있음을 보였다.

Keywords

References

  1. 충남과학연구지 v.19 no.2 평균장이론 신경회로망의 수량화문제에의 응용 김웅환;이경희;이원돈
  2. 충남과학연구지 v.19 no.2 Coulomb Energy Network 에서 Temperature 변화에 따른 학습 김응환;최희숙;이원돈
  3. Technical Report, No. 9201 A Clustering Method of Ambiguous Representation 이석훈;김웅환
  4. Proceedings of the International Society for Optical Engineering v.218-247 Associative Learning, Adaptive Pattern Recognition and Cooperative Decision Making by Neural Networks Carpenter,G.A.;Grossberg,S.
  5. ARO Technical Report Dembo,A.;Zeitouni,O.
  6. Algorithms for Clustering Data Jain,A.;Dubes,R.
  7. Ph.D Dissertation, Department of Computer Science, University of South Carolina Properties and Characteristics of Self-Organizing Neural Networks for Unsupervised Pattern Recognition Kim,D.S.
  8. Proceedings of the International Joint Conference on Neural Networks v.Ⅰ Learning of the Coulomb Energy Network on the Variation of the Temperature function Kim,Y.H.;Choi,H.S.;Lee,K.H.;Lee,W.D.
  9. Proceedings of the International Joint Conference on Neural Networks v.Ⅰ Pattern classifying Neural Network based on Fisher's Linear Discriminant function Kim,Y.H.;Lee,J.C.;Lee,W.D.;Lee,S.H.
  10. Self-Organization and Associative Memory(Second Edition) Kohonen,T.
  11. IEEE Trans. on Neural Networks v.1 no.1;March Unsupervised Learning in Noise Kosko,B.
  12. 1991 Japanese Neural Network Society(JNNS) Pattern classifying Neural Network based on an Entropy Measure Lee,S.H.;Lee,J.C.;Kim,Y.H.;Lee,W.D.
  13. IEEE ASSP Magazine no.April An introduction to computing with Neural Nets Lippmann,R.P.
  14. International Conference on Neural Network v.Ⅰ Learning international representations in the coulomb energy network Scofield,C.L.
  15. SPSS/PC+ advanced statistics