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Tytuł artykułu

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

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Języki publikacji
EN
Abstrakty
EN
This article presents the results of a survey regarding architects’ expectations towards software for automated floor plan generation (AFPG) and optimisation processes in architectural design. More than 150 practising architects from Poland and abroad took part in the survey. Survey results were then extracted, ordered and interpreted with the use of data mining. The survey structure, methodology and analytical tools used are described in the paper.
Twórcy
  • Wroclaw University of Science and Technology
  • Faculty of Architecture, Wroclaw University of Science and Technology
  • Faculty of Computer Science and Management, Wroclaw University of Science and Technology
Bibliografia
  • 1] ArchitectureQuote. 2019. 100 Best Architecture Firms in the World [2019]. ArchitectureQuote. https://architecturequote.com/blog/100-best-architecture-firms-in-the-world/.
  • [2] Bujak, Ł. 2008. Drzewa decyzyjne. Toruń: Wyd. UMK.
  • [3] 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 Comput-er-Aided Architectural Design Research in Asia (CAADRIA) 2017, The Association for Computer-Aided Architectural De-sign Research in Asia (CAADRIA), 387−397.
  • [4] DesignRulz. 2017. Top 100 Most Innovative Architecture Firms to Work For. DesignRulz. https://www.designrulz.com/best-architecture-firms/.
  • [5] Flach, P.A. and Lachiche, N. 2001. Confirmation-Guided Discovery of First-Order Rules with Tertius. Machine Learn-ing 42, 1, 61−95.
  • [6] 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.
  • [7] 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.
  • [8] Mangiafico, S.S. 2016. R Handbook: Measures of Association for Nominal Variables. rcompanion.org. https://rcompan-ion.org/handbook/H_10.html.
  • [9] 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.
  • [10] 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.
  • [11] Nisztuk, M. and Myszkowski, P.B. 2019. Hybrid Evolutionary Algorithm applied to Automated Floor Plan Generation. International Journal of Architectural Computing.
  • [12] Quinlan, J.R. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
  • [13] R Core Team. 2019. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
  • [14] Słyk, J. 2014. Eksperyment, symulacja-techniki projektowe i wyzwania edukacyjne. Kwartalnik Architektury i Urbanisty-ki 59, 2, 11−24.
  • [15] 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 Envi-ronment 4, 11−18.
  • [16] Słyk, J. 2019. Architektura Eksperymentalna? Rzut Kwartalnik Architektoniczny 3, 1.
  • [17] Vitruvius Pollio and Morgan, M.H. 1960. Vitruvius: the ten books on architecture. Dover Publications, New York.
  • [18] 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.
  • [19] Wortmann, T. 2019. Architectural Design Optimization – Results from a User Survey. KnE Social Sciences, 473−483.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ba69dfd1-1f65-4dc8-b898-aa8229ac1180
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