Using Machine Learning Techniques to Predict Esthetic Features of Buildings-Reference-Cited by-同舟云学术

Using Machine Learning Techniques to Predict Esthetic Features of Buildings

Published:2021-09 Issue:3 Volume:27 Page:04021023
ISSN:1076-0431
Container-title:Journal of Architectural Engineering
language:en
Short-container-title:J. Archit. Eng.

Author:

Aydin Yusuf Cihat¹,Mirzaei Parham A.²,Hale Jonathan³^ORCID

Affiliation:

1. Doctor, Faculty of Engineering, Univ. of Nottingham, University Park, Nottingham NG7 2RD, UK.

2. Assistant Professor, Faculty of Engineering, Univ. of Nottingham, University Park, Nottingham NG7 2RD, UK (corresponding author).

3. Professor of Architectural Theory, Faculty of Engineering, Univ. of Nottingham, University Park, Nottingham NG7 2RD, UK. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Visual Arts and Performing Arts,Building and Construction,Civil and Structural Engineering,Architecture

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29AE.1943-5568.0000477

Reference36 articles.

1. Artificial intelligence in architecture: Generating conceptual design via deep learning;As I.;Int. J. Archit. Comput.,2018

2. Wind-driven ventilation improvement with plan typology alteration: A CFD case study of traditional Turkish architecture

3. Aydin, Y. C., and P. A. Mirzaei. 2018. “How window features impact energy efficiency and marketability of residential buildings?” In Proc., 17th Int. Conf. on Sustainable Energy Technologies – SET 2018, Wuhan, China.

4. A novel mathematical model to measure individuals’ perception of the symmetry level of building facades;Aydin Y. C.;Archit. Eng. Des. Manage.,2020

5. On the relationship between building energy efficiency, aesthetic features and marketability: Toward a novel policy for energy demand reduction;Aydin Y. C.;Energy Policy,2019

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