Optimal algorithm of data streams clustering based on density

To deal with outliers of data streams,the density-based clustering algorithm of data streams DenStream is improved,and double detection time strategy(DDTS) is proposed.The strategy maintains and deletes clusters dynamically.In addition,with the purpose of high cluster quality and efficiency,potential outlier points are preserved by DDTS.Theory and practice show that the improved algorithm possesses good practicality and effectiveness and achieves a higher quality of clustering.