论文信息 - The Fuzzy Hierarchical Cross-Clustering Algorithm. Improvements and Comparative Study

The Fuzzy Hierarchical Cross-Clustering Algorithm. Improvements and Comparative Study

The aim of this paper is to introduce a way to improve the behavior of the Fuzzy Hierarchical Cross-Clustering Algorithm. The Simultaneous Fuzzy n-Means Algorithm produces fuzzy n-partitions of objects and characteristics, but it does not offer a modality to associate each fuzzy set of objects to a fuzzy set of characteristics. Based on our previous experience we are able to propose such an association. In the second part of the paper we will study the behavior of the Fuzzy Hierarchical Cross-Clustering Algorithm using both the original and the Improved Simultaneous Fuzzy n-Means Algorithm.

Horia F. Pop | Horia F. Pop | Costel Sârbu | C. Sârbu

[1] Horia F. Pop,et al. A study of Roman pottery (terra sigillata) using hierarchical fuzzy clustering , 1995 .

[2] Horia F. Pop,et al. A Fuzzy Cross-Classification of the Chemical Elements, Based on Their Physical, Chemical, and Structural Features , 1996, J. Chem. Inf. Comput. Sci..

[3] Horia F. Pop,et al. A new fuzzy regression algorithm. , 1996, Analytical chemistry.

[4] D. Dimitrescu,et al. Hierarchical pattern classification , 1988 .

[5] Dumitru Dumitrescu,et al. Fuzzy hierarchical cross-classification of Greek muds , 1995, J. Chem. Inf. Comput. Sci..

[6] Horia F. Pop,et al. A Fuzzy Divisive Hierarchical Clustering Algorithm for the Optimal Choice of Sets of Solvent Systems , 1994 .

[7] Dumitru Dumitrescu,et al. A Fuzzy Classification of the Chemical Elements , 1996, J. Chem. Inf. Comput. Sci..