Spatiotemporal Data Mining with Cellular Automata

  • Karl Fu
  • Yang Cai
Conference paper

DOI: 10.1007/11758501_158

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3991)
Cite this paper as:
Fu K., Cai Y. (2006) Spatiotemporal Data Mining with Cellular Automata. In: Alexandrov V.N., van Albada G.D., Sloot P.M.A., Dongarra J. (eds) Computational Science – ICCS 2006. ICCS 2006. Lecture Notes in Computer Science, vol 3991. Springer, Berlin, Heidelberg

Abstract

In this paper, we describe a cellular automata model for predicting biological spatiotemporal dynamics in an imagery data flow. The Bayesian probability-based algorithm is used to estimate the algal formation in a two-dimensional space. The dynamics of the cellular artificial life is described with diffusion, transport, collision and deformation. We tested the model with the historical data, including parameters, such as time, position and temperature.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Karl Fu
    • 1
  • Yang Cai
    • 1
  1. 1.Visual Intelligence Studios, Cylab, CIC-2218Carnegie Mellon UniversityPittsburghUSA

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