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Neuro-Fuzzy Models and Tobacco Control

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Proceedings of the European Computing Conference

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 27))

Abstract

This paper presents neuro-fuzzy models applications appropriate for tobacco control: the fuzzy control model, Adaptive Network-Based Fuzzy Inference System, Evolving Fuzzy Neural Network models, and EVOlving POLicies. We propose further the use of Fuzzy Causal Networks to help tobacco control decision makers develop policies and measure their impact on social regulation.

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Author information

Authors and Affiliations

  1. Department of Management, Monash University, 26 Sir John Monash Drive, Caulfield East, VIC 3145, Australia

    Sonja Petrovic-Lazarevic & Jian Ying Zhang

Authors
  1. Sonja Petrovic-Lazarevic
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  2. Jian Ying Zhang
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Corresponding author

Correspondence to Sonja Petrovic-Lazarevic .

Editor information

Editors and Affiliations

  1. Military Institutes of University, Hellenic Naval Academy, Leoforos Chatzikyriakou, Piraeus, 185 39, Greece

    Nikos Mastorakis

  2. Dept. Theoretical Electrical, Technical University of Sofia, Kl. Ohridski St. 8, Sofia, 1000, Bulgaria

    Valeri Mladenov

  3. Roumelis 6, Vrilissia, 152 35, Greece

    Vassiliki T. Kontargyri

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© 2009 Springer Science+Business Media, LLC

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Petrovic-Lazarevic, S., Zhang, J.Y. (2009). Neuro-Fuzzy Models and Tobacco Control. In: Mastorakis, N., Mladenov, V., Kontargyri, V. (eds) Proceedings of the European Computing Conference. Lecture Notes in Electrical Engineering, vol 27. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-84814-3_3

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  • DOI: https://doi.org/10.1007/978-0-387-84814-3_3

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-84813-6

  • Online ISBN: 978-0-387-84814-3

  • eBook Packages: EngineeringEngineering (R0)

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