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Information Theory Inspired Weighted Immune Classification Algorithm

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Artificial Intelligence and Soft Computing – ICAISC 2008 (ICAISC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5097))

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Abstract

This article presents an example of a handwritten numbers classifier based on the immune system. We study mutual relations between the system operation parameters, as well as new mechanisms introduced in order to make the system work faster. To achieve the goal the weights inspired by the information theory have been inserted to the immune system.

This work was partly supported by the Foundation for Polish Science (Professorial Grant 2005-2008) and Polish Ministry of Science and Higher Education (Habilitation Project 2008-2010, Special Research Project 2006-2009, Polish-Singapore Research Project 2008-2010, Research Project 2008-2010).

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References

  1. Alpaydin, E., Kaynak, C., Alimoglu, F.: Cascading Multiple Classifiers and Representations for Optical and Pen-Based Handwritten Digit Recognition. In: IWFHR, Amsterdam, The Netherlands (September 2000)

    Google Scholar 

  2. Alimoglu, F., Alpaydin, E.: Combining Multiple Representations for Pen-based Handwritten Digit Recognition. ELEKTRIK: Turkish Journal of Electrical Engineering and Computer Sciences 9(1), 1–12 (2001)

    Google Scholar 

  3. Alpaydin, E., Alimoglu, F.: Optical Recognition of Handwritten Digits, http://www.ics.uci.edu/~mlearn/databases/optdigits/

  4. Alpaydin, E., Kaynak, C.: Pen- Based Recognition of Handwritten Digits, http://www.ics.uci.edu/~mlearn/databases/pendigits/

  5. de Castro, L.N., von Zuben, F.J.: Learning and optimization using the clonal selection principle. IEEE Transactions on Evolutionary Computation, Special Issue on Artifical Immune System 6, 239–251 (2002)

    Google Scholar 

  6. Chen, S.-M.: Weighted fuzzy reasoning using weighted fuzzy Petri nets. IEEE Transactions on Knowledge and Data Engineering 14(2), 386–397 (2002)

    Article  Google Scholar 

  7. Farmer, J.D., Packard, N.H., Perelson, A.S.: The immune system, adaptation, and machine learning. Physica D 22, 187–204 (1986)

    Article  MathSciNet  Google Scholar 

  8. Garret, S.M.: How do we evaluate artificial immune systems? Evolutionary Computation 13, 145–178 (2005)

    Article  Google Scholar 

  9. Hofmeyr, S.A., Forrest, S.: Architecture for an artificial immune system. Evolutionary Computation 8, 443–473 (2000)

    Article  Google Scholar 

  10. Osmond, D.G.: The turn-over of B cell populations. Immunology Today 14, 34–37 (1993)

    Article  Google Scholar 

  11. Rafajłowicz, E., Pawlak, M., Steland, A.: Nonlinear image processing and filtering: A unified approach based on vertically weighted regression. Int. J. Appl. Math. Comput. Sci. 18(1), 49–61 (2008)

    Article  MathSciNet  Google Scholar 

  12. Rutkowski, L.: Flexible Neuro-Fuzzy Systems. Kluwer Academic Publishers, Dordrecht (2004)

    MATH  Google Scholar 

  13. Rutkowski, L., Cpałka, K.: Flexible neuro-fuzzy systems. IEEE Trans. Neural Netw. 14(3), 554–574 (2003)

    Article  Google Scholar 

  14. Rutkowski, L., Cpałka, K.: Designing and learning of adjustable quasi-triangular norms with applications to neuro-fuzzy systems. IEEE Trans. Fuzzy Syst. 13(1), 140–151 (2005)

    Article  Google Scholar 

  15. Shannon, C.E.: A Mathematical Theory of Communication. Bell System Technical Journal 27, 379–423, 623–656 (1948)

    MathSciNet  Google Scholar 

  16. Shannon, C.E., Weaver, W.: The Mathematical Theory of Communication. Univ of Illinois Press (1949)

    Google Scholar 

  17. Solomon, E.P., Berg, L.R., Martin, D.W.: Biology, 6th edn. Thomson Brooks/Cole (2001)

    Google Scholar 

  18. Yeung, D.S., Ysang, E.C.C.: A multilevel weighted fuzzy reasoning algorithm for expert systems. IEEE Transactions on Systems, Man and Cybernetics, Part A 28(2), 149–158 (1998)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Czȩstochowa University of Technology, Al. Armii Krajowej 36, 42-200, Czȩstochowa, Poland

    Maciej Morkowski & Robert Nowicki

  2. Department of Artificial Intelligence, Academy of Humanities and Economics in Łódź, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Robert Nowicki

Authors
  1. Maciej Morkowski
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  2. Robert Nowicki
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Editor information

Leszek Rutkowski Ryszard Tadeusiewicz Lotfi A. Zadeh Jacek M. Zurada

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Morkowski, M., Nowicki, R. (2008). Information Theory Inspired Weighted Immune Classification Algorithm. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_63

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  • DOI: https://doi.org/10.1007/978-3-540-69731-2_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69572-1

  • Online ISBN: 978-3-540-69731-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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