Research on Green Design Optimization of Ethnic Minority Architecture in Guangxi Based on Machine Learning

Lu Cong, Huang Nenglang, Wu Yang
Proceedings of 2024 International Conference on Machine Learning and Intelligent Computing, PMLR 245:366-372, 2024.

Abstract

Guangxi Zhuang Autonomous Region, as one of China’s ethnic minority areas, possesses rich heritage resources in ethnic architecture, with dual objectives of cultural preservation and ecological sustainability. This paper explores the design principles of ethnic minority architecture in Guangxi, investigates the relationship between architecture and climate adaptability, and integrates them with digital fabrication technology. Utilizing parametric platforms and performance simulation tools, the study examines the climate adaptability of ethnic minority architecture in Guangxi. Through machine learning, models for lighting, thermal, and humidity environments specific to Guangxi’s ethnic minority regions are developed. Optimization parameters for architectural design are proposed, and the reliability and accuracy of the models are demonstrated through training and testing, providing ecological design optimization strategies and references for future research on green architecture in ethnic minority areas.

Cite this Paper

BibTeX
@InProceedings{pmlr-v245-cong24a, title = {Research on Green Design Optimization of Ethnic Minority Architecture in Guangxi Based on Machine Learning }, author = {Cong, Lu and Nenglang, Huang and Yang, Wu}, booktitle = {Proceedings of 2024 International Conference on Machine Learning and Intelligent Computing}, pages = {366--372}, year = {2024}, editor = {Nianyin, Zeng and Pachori, Ram Bilas}, volume = {245}, series = {Proceedings of Machine Learning Research}, month = {26--28 Apr}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v245/main/assets/cong24a/cong24a.pdf}, url = {https://proceedings.mlr.press/v245/cong24a.html}, abstract = {Guangxi Zhuang Autonomous Region, as one of China’s ethnic minority areas, possesses rich heritage resources in ethnic architecture, with dual objectives of cultural preservation and ecological sustainability. This paper explores the design principles of ethnic minority architecture in Guangxi, investigates the relationship between architecture and climate adaptability, and integrates them with digital fabrication technology. Utilizing parametric platforms and performance simulation tools, the study examines the climate adaptability of ethnic minority architecture in Guangxi. Through machine learning, models for lighting, thermal, and humidity environments specific to Guangxi’s ethnic minority regions are developed. Optimization parameters for architectural design are proposed, and the reliability and accuracy of the models are demonstrated through training and testing, providing ecological design optimization strategies and references for future research on green architecture in ethnic minority areas.} }
Endnote
%0 Conference Paper %T Research on Green Design Optimization of Ethnic Minority Architecture in Guangxi Based on Machine Learning %A Lu Cong %A Huang Nenglang %A Wu Yang %B Proceedings of 2024 International Conference on Machine Learning and Intelligent Computing %C Proceedings of Machine Learning Research %D 2024 %E Zeng Nianyin %E Ram Bilas Pachori %F pmlr-v245-cong24a %I PMLR %P 366--372 %U https://proceedings.mlr.press/v245/cong24a.html %V 245 %X Guangxi Zhuang Autonomous Region, as one of China’s ethnic minority areas, possesses rich heritage resources in ethnic architecture, with dual objectives of cultural preservation and ecological sustainability. This paper explores the design principles of ethnic minority architecture in Guangxi, investigates the relationship between architecture and climate adaptability, and integrates them with digital fabrication technology. Utilizing parametric platforms and performance simulation tools, the study examines the climate adaptability of ethnic minority architecture in Guangxi. Through machine learning, models for lighting, thermal, and humidity environments specific to Guangxi’s ethnic minority regions are developed. Optimization parameters for architectural design are proposed, and the reliability and accuracy of the models are demonstrated through training and testing, providing ecological design optimization strategies and references for future research on green architecture in ethnic minority areas.
APA
Cong, L., Nenglang, H. & Yang, W.. (2024). Research on Green Design Optimization of Ethnic Minority Architecture in Guangxi Based on Machine Learning . Proceedings of 2024 International Conference on Machine Learning and Intelligent Computing, in Proceedings of Machine Learning Research 245:366-372 Available from https://proceedings.mlr.press/v245/cong24a.html.

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