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Investigation of the Fuzzy System for the Assessment of Cadastre Operators’ Work

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Advances in Web Intelligence and Data Mining

Part of the book series: Studies in Computational Intelligence ((SCI,volume 23))

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References

  1. Ajith A (2001) Neuro-Fuzzy Systems: Sate-of-the-Art Modelling Techniques. In: Proceedings of the 6th International Conference on Neural Networks 269–276

    Google Scholar 

  2. Cheung W, Pitcher T, Pauly D (2004) A Fuzzy Logic Expert System for Estimating the Intrinsic Extinction Vulnerabilities of Seamount Fishes to Fishing. Fisheries Centre Research Reports 12(5):33–50

    Google Scholar 

  3. Gomez A, Delgado M, Vila M (1999) About the use of fuzzy clustering techniques for fuzzy model identification. Fuzzy Sets and Systems 106(2):179–188

    Article  Google Scholar 

  4. Herrera F (2005) Genetic Fuzzy Systems: Status, Critical Considerations and Future Directions. Journal of Computational Intelligence Research 1(1):59–67

    Google Scholar 

  5. IEC 1131-Programmable Controllers (1997) Part 7-Fuzzy Control Program ming. Committee Draft CD 1.0 (Rel. 19 Jan 97)

    Google Scholar 

  6. Król D, Kukla G S, Lasota T, Trawiński B (2006) Fuzzy Model for the Assessment of Operators’ Work in a Cadastre Information System (to be published

    Google Scholar 

  7. Piegat A (2003) Fuzzy Modelling and Control (in Polish). Akademicka Oficyna Wydawnicza EXIT Warszawa

    Google Scholar 

  8. Saez D, Cipriano A (2001) A new method for structure identification of fuzzy models and its application to a combined cycle power plant. Engineering Intel ligent Systems 9(2):101–107

    Google Scholar 

  9. Xing Zong-Yi, Jia Li-Min, Zhang Yong, Hu Wei-Li, Qin Yong (2005) A Case Study of Data-driven Interpretable Fuzzy Modeling. Acta Automatica Sinica 31(6):815–824

    Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Król, D., Kukla, G., Lasota, T., Trawiński, B. (2006). Investigation of the Fuzzy System for the Assessment of Cadastre Operators’ Work. In: Last, M., Szczepaniak, P.S., Volkovich, Z., Kandel, A. (eds) Advances in Web Intelligence and Data Mining. Studies in Computational Intelligence, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33880-2_14

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  • DOI: https://doi.org/10.1007/3-540-33880-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33879-6

  • Online ISBN: 978-3-540-33880-2

  • eBook Packages: EngineeringEngineering (R0)

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