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CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	caadria2019_491
id	caadria2019_491
authors	Cai, Chenyi, Tang, Peng and Li, Biao
year	2019
title	Intelligent Generation of Architectural layout inheriting spatial features of Chinese Garden Based on Prototype and Multi-agent System - A Case Study on Lotus Teahouse in Yixing
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 291-300
doi	https://doi.org/10.52842/conf.caadria.2019.1.291
summary	This study presents an approach for the intelligent generation of architectural layout, in which partial space inherits Chinese garden spatial features. The approach combines spatial prototype analysis and evolutionary optimization process. On one hand, from the perspective of shape grammar, this paper both analyzes and abstracts the spatial prototype that describes the spatial characteristics of Chinese gardens, including the organization system of architecture and landscape, with the spatial sequences along the tourism orientation. On the other hand, taking the design task of Lotus teahouse as an example, a typical spatial prototype is selected to develop the generative intelligent experiment to achieve the architectural layout, in which the spatial prototype is inherited. Through rule-making and parameter adjustment, the spatial prototype will eventually be transformed into a computational model based on the multi-agent system. Hence, the experiment of intelligent generation of architectural layout is carried out under the influence of the function, form and environmental factors; and a three-dimensional conceptual model that inherits the Chinese garden spatial prototype is obtained ultimately.
keywords	Chinese garden; Architectural layout; Spatial prototype; Multi-agent system; Intelligent generation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	caadria2019_422
id	caadria2019_422
authors	Wang, Xiao, Tang, Peng and Shi, Xing
year	2019
title	Analysis and Conservation Methods of Traditional Architecture and Settlement Based on Knowledge Discovery and Digital Generation - A Case Study of Gunanjie Street in China
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 757-766
doi	https://doi.org/10.52842/conf.caadria.2019.1.757
summary	In the conservation plan of traditional architecture and settlement, the mismatch between design and construction is an inevitable problem. The mismatch commonly shows as the variations in the cognition of the traditionality of architecture feature. In most cases, the evaluation of historical feature is made based on designers' subjective perception, experience, and understanding of the traditional style. Also, without an appropriate guide and unified control, it could make the conservation plan less efficient in practice. Therefore, a quantitative method for conservation plan is needed, which is expected to be effective especially for massive non-key but traditional ordinary buildings. In this study on Gunanjie Street, in Yixing, China, a new method of feature analysis and generative design was developed to regenerate the district. The proposed method first adapted new data acquisition and processing techniques to gather information and build the database. Cognition investigation and morphology analysis were then implemented to quantify and evaluate the features of historical characteristics, as well as the knowledge discovery tools, were further used to abstract the rules of the traditional facade. With these phases, the proposed method was able to generate the referable design schemes quantitatively and establish generally accepted conservation plans and guidelines.
keywords	Traditional architecture and settlement; historical feature; Knowledge Discovery; digital generation; conservation
series	CAADRIA
email
last changed	2022/06/07 07:58

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