Academic Journal

Prediction of human restorative experience for human-centered residential architecture design : a non-immersive VR–DOE-based machine learning method

التفاصيل البيبلوغرافية
العنوان: Prediction of human restorative experience for human-centered residential architecture design : a non-immersive VR–DOE-based machine learning method
المؤلفون: Zhang, Y, Xiao, B, Al-Hussein, M, Li, X
المساهمون: Department of Building and Real Estate
بيانات النشر: Elsevier
سنة النشر: 2022
المجموعة: Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)
مصطلحات موضوعية: Built environment, Design of experiment, Human-centered design, Machine learning, Prediction model, Residential design, Restorative experience, Virtual reality
الوصف: 202203 bcvc ; Accepted Manuscript ; Others ; Alberta Innovates; National Natural Science Foundation of China ; Published ; Green (AAM)
نوع الوثيقة: article in journal/newspaper
اللغة: English
تدمد: 0926-5805
1872-7891
Relation: http://hdl.handle.net/10397/92287; 136; 2-s2.0-85125665944; 104189; a1205-01; 44165
DOI: 10.1016/j.autcon.2022.104189
الاتاحة: http://hdl.handle.net/10397/92287
https://doi.org/10.1016/j.autcon.2022.104189
Rights: © 2022 Elsevier B.V. All rights reserved. ; © 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. ; The following publication Zhang, Y., Xiao, B., Al-Hussein, M., & Li, X. (2022). Prediction of human restorative experience for human-centered residential architecture design: A non-immersive VR–DOE-based machine learning method. Automation in Construction, 136, 104189 is available at https://dx.doi.org/10.1016/j.autcon.2022.104189.
رقم الانضمام: edsbas.8B786B65
قاعدة البيانات: BASE
الوصف
تدمد:09265805
18727891
DOI:10.1016/j.autcon.2022.104189