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The outline of the expert system for the design of experiment

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The design of experiment (DoE) is a methodology originated from early 1920s when Fisher’s papers created the analysis of variance and first known experimental designs: latin squares. It is focused on a construction of empirical models based on measurements obtained from specifically structured and driven experiments. Its development resulted in the constitution of four distinctive branches recognized by the industry: factorials (full or fractional), Taguchi’s robust design, Shainin’s Red-X® and a response surface methodology (RSM). On one hand, the well-known success stories of this methodology implementations promise great benefits, while on other hand, the mathematical complexity of mathematical and statistical assumptions very often lead to improper use and wrong inferences. The possible solution to avoid such mistakes is the expert system supporting the design of experiments and subsequently the analysis of obtained data. The authors propose the outline of such system and provides the general analysis of the ontology and related inference rules.
Rocznik
Tom
Strony
43--48
Opis fizyczny
Bibliogr. 25 poz., rys.
Twórcy
autor
  • Cracow University of Technology, Faculty of Mechanical Engineering, Al. Jana Pawła II 37, 31-864 Kraków, Poland
  • Cracow University of Technology, Faculty of Mechanical Engineering, Al. Jana Pawła II 37, 31-864 Kraków, Poland
Bibliografia
  • 1. Agresti, A., 2002. Categorical data analysis. John Wiley & Sons, Hoboken.
  • 2. Bhote, K., 1991. World Class Quality. AMACOM, New York.
  • 3. Box, G.E.P., Wilson, K.B., 1951. On the Experimental Attainment of Optimum Conditions. Journal of the Royal Statistical Society B 13, 1-45.
  • 4. Everitt, B.S., Landau, S., Leese, M., Stahl, D., 2011. Cluster analysis 5th edition. John Wiley & Sons, Hoboken.
  • 5. Fisher, R., 1918. Studies in Crop Variation. I. An examination of the yield of dressed grain from Broadbalk. Journal of Agricultural Science 11, 107-135.
  • 6. Fisher, R.A., 1925. Statistical Methods for Research Workers. Oliver & Boyd Press, Edinburgh.
  • 7. Fisher, R.A., 1935. The Design of Experiments. Oliver & Boyd Press, Edinburgh.
  • 8. Gentle, J.E., Hardle, W.K., 2012. Handbook of Computational Statistics. Springer-Verlag, Berlin-Heidelberg.
  • 9. Hilbe, J.M., 2009. Logistic regression models. CRC Press, Boca Raton.
  • 10. Hosmer, D.W., Lemeshow, S., 2000. Applied Logistic Regression. John Wiley & Sons, Hoboken.
  • 11. Izenman, A.J., 2008. Modern multivariate statistical techniques: regression, classification, and manifold learning. Springer, New York.
  • 12. Jackson, P., 1999. Introduction to expert systems. Addison-Wesley, Harlow, England.
  • 13. John, P.W.M., 1998. Statistical design and analysis of experiments. SIAM, Philadelphia.
  • 14. Jolliffe, I.T., 2010. Principal component analysis. Springer, New York.
  • 15. Liebowitz, J. (ed.), 1998. The Handbook of applied expert systems. CRC Press, Boca Raton.
  • 16. Montgomery, D.C., 1997. Introduction to Statistical Quality Control. John Wiley & Sons, Hoboken.
  • 17. Montgomery, D.C., 2008. Design and Analysis of Experiments. John Wiley & Sons, Hoboken.
  • 18. Niewiadomski, A., 2008. Methods for the linguistic summarization of data: applications of fuzzy sets and their extensions. AOW Exit, Warszawa, Poland.
  • 19. Phadke, M.S., 1989. Quality Engineering Using Robust Design. Prentice 19. Hall International, Inc., London.
  • 20. Plackett, R.L., Burman, J.P., 1946. The design of optimum multifactorial experiments. Biometrika 33, 305-325.
  • 21. Scheffé, H., 1958. Experiments with Mixtures. Journal of the Royal Statistical Society B 20, 344-360.
  • 22. Siegel, S., Tukey, J.W., 1960. A nonparametric sum of ranks procedure for relative spread in unpaired samples. Journal of the American Statistical Association 55 (291), 429-445.
  • 23. Siler, W., Buckley, J.J., 2005. Fuzzy expert systems and fuzzy reasoning. John Wiley & Sons, Hoboken.
  • 24. Stevens, S.S., 1946. On the theory of scales of measurements. Science 103, 677-680.
  • 25. Yates, F., 1935. Complex experiments. Journal of the Royal Statistical Society Suppl. 2, 181-247.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-be9e8053-3a01-4f50-9ce6-028e4b887bab
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