Song, Yu-ChenYu-ChenSongO'Grady, Michael J.Michael J.O'GradyO'Hare, G. M. P. (Greg M. P.)G. M. P. (Greg M. P.)O'HareWang, WeiWeiWang2009-08-102009-08-102008 by Th2008-12978-0-7695-3514-2http://hdl.handle.net/10197/1346Paper presented at the International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA 2008), 10-12 December 2008 - Vienna, AustriaThis paper analyses the advantages and disadvantages of the K-means algorithm and the DENCLUE algorithm. In order to realise the automation of clustering analysis and eliminate human factors, both partitioning and density-based methods were adopted, resulting in a new algorithm – Clustering Algorithm based on object Density and Direction (CADD). This paper discusses the theory and algorithm design of the CADD algorithm. As an illustration of its applicability, CADD was used to cluster real world data from the geochemistry domain.393866 bytesapplication/pdfenCluster analysis--Computer programsAlgorithmsData miningConference Publication10.1109/CIMCA.2008.34https://creativecommons.org/licenses/by-nc-sa/1.0/