Clustering of parameters on the basis of correlations via simulated annealing

Control and Cybernetics

Volumn 25, Issue 1, 1996, Pages 55-73

  Dzemyda, Gintautas ^a  

^a VILNIUS UNIVERSITY   (Lithuania)

Author keywords

Combinatorial optimization; Data analysis; Parameter clustering; Simulated annealing

Indexed keywords

EID: 0030550789     PISSN: 03248569     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (21)

1. ANDERBERG, M.R. (1973) Cluster Analysis for Applications. Academic Press, New York.
2. BRAVERMAN, E.M. (1970) Methods of extremal grouping of parameters and the problem of apportionment of essential factors, Automatika i Telemechanika, 1, 123-132 (in Russian).
3. BRAVERMAN, E.M. and MUCHNIK, I.B. (1983) The Structural Methods for Empirical Data Processing. Nauka, Moscow (in Russian).
4. DIDAY, E. (1986) Canonical analysis from the automatic classification point of view. In: J.W. Owsiński, ed., Control and Cybernetics, Special Issue on Optimization Approaches in Clustering, 15, 2, 115-137.
5. DZEMYDA, G. (1987) On the extremal parameter grouping. In: A. Žilinskas, ed., Teorija Optimal'nych Reshenij, Vol. 12, Inst. Math. Cybern. Lith. Acad. Sci., Vilnius, 28-42 (in Russian).
6. DZEMYDA, G. (1988) The algorithms of extremal parameter grouping. In: A. Sydow, S.G. Tzafestas and R. Vichnevetsky, eds., Mathematical Research, Band 46, Akademie-Verlag, Berlin, 133-136.
7. DZEMYDA, G. (1990) Grouping on the sphere. In: Teorija Optimal'nych Reshenij, Vol. 14, Vilnius, 22-40 (in Russian).
8. DZEMYDA, G. and VALEVIČIENE, J. (1988) The extremal parameter grouping in cluster analysis. In: Teorija Optimal'nych Reshenij, Vol. 13, Vilnius, 30-53 (in Russian).
9. DZEMYDA, G. and SENKIENĖ, E. (1992) Simulated annealing for parameter grouping. In: Trans. of the 11th Prague Conf. on Information Theory, Statistical Decision Functions, Random Processes, ACADEMIA, Prague, 373-383.
10. DZEMYDA, G., SENKIENĖ E. and VALEVIČIENĖ, J. (1990) On the problem of parameter grouping. In: H.-M. Voigt, H. Mühlenbein and H.-P. Schwefel, eds., Evolution and Optimization'89. Selected Papers on Evolution Theory, Combinatorial Optimization, and Related Topics, Akademie-Verlag, Berlin, 216-224.
11. EGLESE, R.W. (1990) Simulated annealing: a tool for operational research. European Journal of Operational Research, 46, 271-281.
12. HARMAN, H.H. (1976) Modern Factor Analysis, 3rd ed. University of Chicago Press, Chicago.
13. HARTIGAN, J. (1975) Clustering Algorithms. Wiley - Interscience, New York.
14. KIRKPATRICK, S., GELATT, C.D. and VECCHI, M.P. (1983) Optimization by simulated annealing. Science, 220, 4598, 671-680.
15. LUMELSKY, V.Y. (1970) Grouping of parameters on the basis of communication matrix. Automatika i Telemechanika, 1, 133-143 (in Russian).
16. MEZZICH, J.E. and SOLOMON, H. (1980) Taxonomy and Behavioral Science, Comparative Performance of Grouping Methods. Academic Press.
17. MITRA, D., ROMEO, F. and SANGIOVANNI-VINCENTELLI, A. (1986) Convergence and finite-time behavior of simulated annealing. Adv. Appl. Prob., 18, 3, 747-771.
18. OWSIŃSKI, J.W. ed. (1986) Control and Cybernetics, Special Issue on Optimization Approaches in Clustering, 15, 2.
19. SAS User's Guide: Statistics (1982) SAS Institute Inc, Cary.
20. SPÄTH, H. (1980) Cluster Analysis Algorithms for Data Reduction and Classification of Objects. Ellis Horwood.
21. TRZEBIATOWSKI, G.W. (1985) Thermodynamic simulation procedure for partitioning problems. In: H.-M. Voigt, ed., Informatis: Informationen-Reporte, 1, 12, Institut für Informatik und Rechentechnik, Berlin, 86-96.