Design guidelines for automated floor plan generation applications – target group survey, results and reflections

ArchitectureQuote. 2019. 100 Best Architecture Firms in the World [2019]. ArchitectureQuote. https://architecturequote.com/blog/100-best-architecture-firms-in-the-world/.
  Google Scholar

Bujak, Ł. 2008. Drzewa decyzyjne. Toruń: Wyd. UMK.
  Google Scholar

Cichocka, J., Browne, W., and Rodriguez Ramirez, E. 2017. Optimization in the architectural practice. An International Survey. Protocols, Flows and Glitches, Proceedings of the 22nd International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) 2017, The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), 387–397.
  Google Scholar

DesignRulz. 2017. Top 100 Most Innovative Architecture Firms to Work For. DesignRulz. https://www.designrulz.com/best-architecture-firms/.
  Google Scholar

Flach, P.A. and Lachiche, N. 2001. Confirmation-Guided Discovery of First-Order Rules with Tertius. Machine Learning 42, 1, 61–95.
  Google Scholar

Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., and Witten, I.H. 2009. The WEKA Data Mining Software: An Update. SIGKDD Explor. Newsl. 11, 1, 10–18.
  Google Scholar

Lynch, P. 2017. These are the Top 300 Architecture Firms in the US for 2017. ArchDaily. http://www.archdaily.com/876808/these-are-the-top-300-architecture-firms-in-the-us-for-2017.
  Google Scholar

Mangiafico, S.S. 2016. R Handbook: Measures of Association for Nominal Variables. rcompanion.org. https://rcompanion.org/handbook/H_10.html.
  Google Scholar

Nisztuk, M., Kościuk, J., and Myszkowski, P.B. 2019. The survey data and correlation graphics. http://elisi.pl/wp-content/uploads/2020/01/survey_answers_nominal_values.zip.
  Google Scholar

Nisztuk, M. and Myszkowski, P.B. 2017. Usability of contemporary tools for the computational design of architectural objects: Review, features evaluation and reflection. International Journal of Architectural Computing, 58–84.
  Google Scholar

Nisztuk, M. and Myszkowski, P.B. 2019. Hybrid Evolutionary Algorithm applied to Automated Floor Plan Generation. International Journal of Architectural Computing.
DOI: https://doi.org/10.1177/1478077119832982   Google Scholar

Quinlan, J.R. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
  Google Scholar

R Core Team. 2019. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
  Google Scholar

Słyk, J. 2014. Eksperyment, symulacja-techniki projektowe i wyzwania edukacyjne. Kwartalnik Architektury i Urbanistyki 59, 2, 11–24.
  Google Scholar

Słyk, J. 2015. Methodology of architectural design and rules of cooperation in the digital environment. Augmented space as a field of research and alternative environment for architectural creation. Architecture Civil Engineering Environment 4, 11–18.
  Google Scholar

Słyk, J. 2019. Architektura Eksperymentalna? Rzut Kwartalnik Architektoniczny 3, 1.
  Google Scholar

Vitruvius Pollio and Morgan, M.H. 1960. Vitruvius: the ten books on architecture. Dover Publications, New York.
  Google Scholar

Witten, I.H., Frank, E., Hall, M.A., and Pal, C.J. 2016. Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
  Google Scholar

Wortmann, T. 2019. Architectural Design Optimization – Results from a User Survey. KnE Social Sciences, 473–483.
  Google Scholar