Utilizing an Enhanced Cellular Automata Model for Data Mining

(*) Corresponding author

Authors' affiliations

DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)


Data mining deals with clustering and classifying large amounts of data, in order to discover new knowledge from the existent data by identifying correlations and relationships between various data-sets. Cellular automata have been used before for classification purposes. This paper presents a cellular automata enhanced classification algorithm for data mining. Experimental results show that the proposed enhancement gives better performance in terms of accuracy and execution time than previous work using cellular automata.
Copyright © 2013 Praise Worthy Prize - All rights reserved.


Cellular Automata; Clustering; Classification; Data Mining; Moore Neighborhood

Full Text:



A cellular automaton model with diffusion for a surface reaction system Original Research Article Chemical Physics, Volume 165, Issue 1, 1 September 1992, Pages 57-63 ,J. Mai and W. von Niessen

Ermentrout GB, Edelstein-Keshet L, 1993, Cellular automata approaches to biological modeling, Journal of Theoretical Biology, 160, 97-133.

Margolus. N, Toffoli.T, Vichniac. G.1986.“Cellular automata supercomputers for fluid –dynamics modeling”. Physics Rev. Lett, 56, :1694-1696, 1986.

Boerlijst M. and Hogeweg P.1991. Self-structuring and selection: In Artifial Life II, pp 159:209, ed. By C. G. Langon, C. Taylor, J. D. Farmer, and S. Rasmussen, editors, Addison.Wesley.

Langton G. G. 1984.Self-reproduction in cellular automata. Physica D 10,10:135-144.

Nagel.K and Scheicher,.A ,1994.Microscopic traffic modeling on parallel high performance computers, Parallel Computing, 20,125:146.

A Schadschneider and M Schreckenberg 1993 J. Phys. A: Math. Gen. 26 L679

Slatnia S., Kazar O., Generalised Evolutionary Cellular Automata Based-approach for Edge Detection, (2008) International Review on Computers and Software (IRECOS), 3 (4), pp. 424 – 428.

Messina, J.P. & Walsh, S.J. 2001. 2.5D Morphogenesis: modeling land use and land cover dynamics in the Ecuadorian Amazon. Plant Ecology, 156: 75-88.

Ward, D. P., Murray, A. T., and Phinn, S. R. (2000) “A stochastically constrained cellular model of urban growth”, Computers, Environment and Urban Systems, Vol.24 No.6, 539-558.

Janko Gravner, David Griffeath. (2010) The One-Dimensional Exactly 1 Cellular Automaton: Replication, Periodicity, and Chaos from Finite Seeds. Journal of Statistical Physics

Online publication date: 10-Dec-2010.

Lindgren .K and Nordahl. M,1990. Universal computation in simple one dimensional cellular automata, Complex Systems, 4 , 299-318.

Morita, K., and Ogiro, T.: Simple universal reversible cellular automata in which reversible logic elements can be embedded, IEICE Trans. on Information and Systems, E87-D, 650-656, 2004.

Offoli. T,1977. Computation construction universality of reversible cellular automata, J. Comput. Syst. Sci., 15 :213-231.

Nordahl. M.G,1989.Formal languages and finite cellular automata.Complex systems, 3:63-78,1989.

Culik II.K, Hurd .L.P, Yu. S, 1990.“Computation theoretic aspects of cellular automata”. Physica D,45:396-403,1990.

Kantardzic, M. (2003) Data mining: Concepts, models, methods and algorithms, USA: John Wiley and Sons

Daniel T. Larose, Data mining methods and models , Wiley IEEE Press,2006.

David Hand, Heikki Mannila, and Padhraic Smyth. Principles of Data Mining. (2001) MIT Press, Cambridge, Massachusetts. ISN 0-262-08290-X

Abraham Silberschatz, Henry F. Korth, S. Sudarshan. Database Systems Concepts Publisher: McGraw-Hill Higher Education 2006 , 1170 Pages ,ISBN: 0072958863

Tom Fawcett .; Data mining with cellular automata , SIGKDD Explorations.; Volume 10.; Issue 1.pp:32-39, July 2008.

P. Kokol, P. Povalej, M. Lenic and G. Stiglic, “Building classifier cellular automata”, Cellular Automata. 6th International Conference on Cellular Automata for Research and Industry, ACRI 2004, Holanda, Springer-Verlag, Lecture Notes in Computer Science Vol. 3305, pp. 823–830, 2004.

Witten, I. and Frank, E. (2011), Data Mining Practical Machine Learning Tools and Techniques, 3rd edition, Elsevier Inc. 2011.

Abu Dalhoum, A.L. and Al-Dhamari, I. (2010), fMRI Brain Data Classification using Cellular Automata, New Aspects of Applied Informatics, Biomedical Electronics, and Informatics and Communications, 2010.

Alfonseca.M, Dalhoum. A.Abu, Ortega. A, 2001 “ Evolving the game of life with a genetic algorithm”, Proceedings of the 3rd Middle East Symposium on Simulation and Modelling (MESM’2001), SCS Publications, p.165-169, ISBN: 1-56555-230-X.

Conway,J.H., Berlekamp,E.R., Guy,R.K.,Winning ways for the mathematical plays. London: Academic Press, Vol 2,Ch.25.

Jecheva V. G., Nikolova E. P., An Adaptive Approach to Anomaly Intrusion Detection Based on Data Mining and String Metrics, (2008) International Review on Computers and Software (IRECOS), 3 (5), pp. 515 – 522.

Sleit, A., Abu Dalhoum, A.L., Al-Dhamari, I. and Awwad, A. (2009), Efficient enhancement on cellular automata for data mining, Proceedings of the 13th WSEAS international conference on Systems, ICS’09.


  • There are currently no refbacks.

Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize