Abstract
According to information theory, a basic concept of the measure of diversity is defined, and a basic inequation of the measure of diversity is discussed and proved, then a concept of increment of diversity is given. The diversity of the information pattern is carried out the analysis. On the basis of theses discussions, the information coefficient measure (ICM) is defined, and a new information clustering algorithm is built up according to the ICM, and then carried out the information clustering analysis for soil fertility data processing in land. Compared with Hierarchical Clustering Algorithm (HCA) traditionally, the result of simulated application shows that the algorithm presented here is feasible and effective.
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© 2007 Springer-Verlag Berlin Heidelberg
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Ding, S., Ning, W., Shi, Z. (2007). Diversity Analysis of Information Pattern and Information Clustering Algorithm. In: Kang, L., Liu, Y., Zeng, S. (eds) Advances in Computation and Intelligence. ISICA 2007. Lecture Notes in Computer Science, vol 4683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74581-5_47
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DOI: https://doi.org/10.1007/978-3-540-74581-5_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74580-8
Online ISBN: 978-3-540-74581-5
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