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An Exploration of Architectural Design Factors with a Consideration of Natural Aspects Based on Web Crawling and Text Mining

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  • Dongmiao Zhao

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266520, China
    School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China)

  • Yufeng Liu

    (School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China)

  • Boyi Pei

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266520, China)

  • Xingtian Wang

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266520, China)

  • Sheng Miao

    (School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China)

  • Weijun Gao

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266520, China
    Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan)

Abstract

Architectural construction is responsible for the consumption of large amounts of resources, so the optimization of architectural design and evaluation is significant for sustainable global development. Most architectural assessments focus on energy conservation, novel materials and eco-friendly strategies, but without agreed indicators and criteria. Since the consideration of natural aspects is somewhat fuzzy and vague, this study utilized data mining technology to explore the major factors related to relationships between buildings and nature. By employing the popular technique of web crawling, this study collected 38,320 architectural descriptions from the “Archdaily”, including descriptions of 11 types of buildings, four of which were taken as typical research representatives. The 100 most frequent words were used to create a word cloud. Using Python script, all of the text was refined and processed with the word2vec model, thereby allowing to conduct Agglomerative Hierarchical Clustering (AHC). The frequency of words related to natural aspects were analyzed within 15 architectural design elements. Different building types in different areas have obvious similarities in terms of design elements, so it is feasible to adopt the same evaluation factors for the building evaluation systems of different regions. This paper mainly focuses on improving the accuracy and validity of assessment by providing basic evaluation indicators that could enhance connections between design and evaluation progress, stimulating the improvement of building environmental performance.

Suggested Citation

  • Dongmiao Zhao & Yufeng Liu & Boyi Pei & Xingtian Wang & Sheng Miao & Weijun Gao, 2022. "An Exploration of Architectural Design Factors with a Consideration of Natural Aspects Based on Web Crawling and Text Mining," Mathematics, MDPI, vol. 10(23), pages 1-20, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:23:p:4407-:d:980835
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    References listed on IDEAS

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    1. Duarte, Rosa & Sánchez-Chóliz, Julio & Sarasa, Cristina, 2018. "Consumer-side actions in a low-carbon economy: A dynamic CGE analysis for Spain," Energy Policy, Elsevier, vol. 118(C), pages 199-210.
    2. Kyunghun Min & Moonyoung Yoon & Katsunori Furuya, 2019. "A Comparison of a Smart City’s Trends in Urban Planning before and after 2016 through Keyword Network Analysis," Sustainability, MDPI, vol. 11(11), pages 1-25, June.
    3. Zhikun Ding & Rongsheng Liu & Zongjie Li & Cheng Fan, 2020. "A Thematic Network-Based Methodology for the Research Trend Identification in Building Energy Management," Energies, MDPI, vol. 13(18), pages 1-33, September.
    4. Nayem Rahman, 2018. "A Taxonomy of Data Mining Problems," International Journal of Business Analytics (IJBAN), IGI Global, vol. 5(2), pages 73-86, April.
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