Application of machine learning based BIM in green public building design

Author:

Wang Dan1,Chang Fuhua1

Affiliation:

1. Zhengzhou Business University

Abstract

Abstract Public activities are mostly carried out in large public buildings, which are closely related to social management. At present, people's demand for public building facilities is increasing, its shape evolution is becoming more complex, and the scientific and technological content of construction related technology is also increasing. The development trend of green public buildings is more and more strong. The traditional building design can not effectively deal with the energy consumption of public buildings and people's demand for their performance. This paper introduces BIM and machine learning technology to study their practical application in the design of green public buildings, and tests the perfect machine learning algorithm. According to the experimental test results, the building energy consumption decreased by 14.3%, the carbon emission decreased by 11.39%, and the absolute value of PMV thermal comfort decreased by 34.7%, which obviously achieved the optimization effect. BIM Technology parametric design can enable the design model formed by conceptual design research to automatically draw construction drawings, detailed drawings and other drawings according to the drawing requirements and standards, thus saving the designer's time and enabling him to transfer the drawing time to the program design. Finally, through experiments, the economy, rationality and operability of using BIM Technology to design green public buildings are confirmed. In this paper, machine learning and BIM Technology are introduced, so as to carry out design research for green public buildings design.

Publisher

Research Square Platform LLC

Reference15 articles.

1. Building and managing facilities for public services;Bennett J;J Public Econ,2006

2. Plan for the Sustainability of Public Buildings through the Energy Efficiency Certification System: Case Study of Public Sports Facilities, Korea;Baek SG;Buildings,2021

3. A modular optimisation model for reducing energy consumption in large scale building facilities;Petri I;Renew Sustain Energy Rev,2014

4. Andalas B, Kusnoputranto H, Koestoer RH (2018) “Developing thermal comfort model through regional budget expenditure analysis towards low energy consumption in public building facility (case object: government building in north and south of Jakarta),” In E3S Web of Conferences, Vol. 74, p. 05001,

5. Preliminary Design of a Smart Logic, Electronic and Green Public Health Questionnaire (SLE-GPHQ) for investigating the proper compatibility between people and green facilities;Nguyen PA;Ann Gen Psychiatry,2018

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3