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- W4385446760 abstract "Architectural aesthetics improve the appearance and value of a building/construction structure based on shape, color, rigidity, etc., appealingly. It includes the maximum safety requirements, durability, structural ability, etc. Therefore the aesthetic implementation requires high-level data accumulation and analysis to satisfy the earlier constraints. This article develops a Selective Aesthetic Application Paradigm (SAAP) for meeting the user criteria in structural design for region-specific adaptability. The proposed paradigm gathers information on the region, people’s expectations, visibility, and structural performance for the aesthetic design application. The proportion considerations in the application are subject to vary according to the region’s adaptability and performance. The proportion of the accumulated data influence in the application is determined using deep learning. In the learning paradigm, two-layered configurations for region-adaptability and performance measures are trained to provide aesthetic design application recommendations. Based on the suggestion and recommendation, the deep learning module is trained to rectify design errors. The training is independent of the previous two error and adaptability verification layers. It is performed using the qualified (selected) aesthetic design with a previous history of user satisfaction." @default.
- W4385446760 created "2023-08-02" @default.
- W4385446760 creator A5064126052 @default.
- W4385446760 date "2023-10-04" @default.
- W4385446760 modified "2023-10-09" @default.
- W4385446760 title "Application of aesthetics in architectural design under the background of big data and artificial intelligence" @default.
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- W4385446760 doi "https://doi.org/10.3233/jifs-231076" @default.
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