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المؤلفIbrahim, Hatem
المؤلفKhattab, Ziad
المؤلفKhattab, Tamer
المؤلفAbraham, Revina
تاريخ الإتاحة2022-10-31T19:21:56Z
تاريخ النشر2022
اسم المنشورJournal of Urban Planning and Development
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1061/(ASCE)UP.1943-5444.0000783
معرّف المصادر الموحدhttp://hdl.handle.net/10576/35663
الملخصThis study aims to visualize the future housing dispersal of expatriates, based on the predicted urban growth in emerging cities. Generalized adversarial networks (GANs) will be utilized to predict the future urban growth of Doha Metropolitan emerging city. The housing dispersal of expatriates will be visualized on the predicted urban growth map to investigate housing preferences, which will be based on Gordon's theory. This study will prove the feasibility of a process approach when practicing the management of urban growth in emerging cities worldwide. It could be a robust solution for the worsening imbalance in the urban morphology of metropolitan cities. The findings of the broad-spectrum housing dispersal guidelines could benefit the policymakers and planners for the realities of spatial patterns and future urban growth. 2021 American Society of Civil Engineers.
راعي المشروعThis paper was made possible by NPRP grant number [NPRP 07 - 960 - 5 - 135] from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the authors.
اللغةen
الناشرAmerican Society of Civil Engineers (ASCE)
الموضوعEmerging cities
Generative adversarial network
Housing dispersal
Machine learning
Urban growth
العنوانGenerative Adversarial Network Approach to Future Sermonizing of Housing Dispersal in Emerging Cities
النوعArticle
رقم العدد1
رقم المجلد148
dc.accessType Abstract Only


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