Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1
Evolutionary Hierarchical Time Series Clustering
Jinan, China
October 16-October 18
ISBN: 0-7695-2528-8
Time series clustering is an important topic, particularly for similarity search amongst long time series such as those arising in bioinformatics. In this paper a new evolutionary algorithm for detecting the hierarchical structure of an input time series data set is proposed. A new linear representation of the cluster structure within the data set is used. Proposed algorithm uses mutation and crossover as (search) variation operators. A new fitness function is proposed.
Citation:
Monica Chis, Crina Grosan, "Evolutionary Hierarchical Time Series Clustering," isda, vol. 1, pp.451-455, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006