Data clustering analysis and simulation research on lithopone calcining process

Absh.mt This paper deeply discusses the hierarchical clustering analysis on lithopone calcining process to discover pacameter correlations. It provides reliable clustering information for process modeling and control. To overcome the deficiencies of conventional hierarchical clustering methods, the paper proposes a new kind of hierarchical clustering method based on artificial immune system. The simulation results verify its good performance.

[1]  Fernando José Von Zuben,et al.  An Evolutionary Immune Network for Data Clustering , 2000, SBRN.

[2]  Jon Timmis.  Visualising Artificial Immune Networks , 2000 .

[3]  A. Hossain.  Statistical analysis and process capability determination of an industrial process , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[4]  Jonathan Timmis,et al.  AINE: an immunological approach to data mining , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[5]  J Timmis,et al.  An artificial immune system for data analysis. , 2000, Bio Systems.

[6]  Richard G. Mathieu,et al.  A methodology for large-scale R&D planning based on cluster analysis , 1993 .

[7]  John E. Hunt,et al.  An adaptive, distributed learning system based on the immune system , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[8]  M. Jambu,et al.  Cluster analysis and data analysis , 1985 .

[9]  Jonathan Timmis.  Artificial immune systems : a novel data analysis technique inspired by the immune network theory , 2000 .