Energy consumption simulation of green building based on BIM system and improved neural network

Author:

Liu Chenguang1

Affiliation:

1. Audit Office, Shandong University of Arts, Jinan, China

Abstract

The construction industry is an indispensable and important support in the national economic industry. The characteristics of the construction industry, such as long production cycle, large number of participants and various types, determine that the development of the construction industry is undoubtedly very difficult. In order to realize the rapid development of the construction industry, transformation is the inevitable development direction of the construction industry in the future, which requires the help of science and technology. With the development of science and technology, information technology and big data have been applied to all walks of life, and these are also important means to support the transformation of the construction industry. In order to achieve green development, reducing energy consumption is an inevitable measure. Energy consumption analysis and reduction can be realized by establishing energy consumption monitoring platform based on big data. The application of BIM system is an information-based energy consumption analysis method. This technology can realize the analysis and prediction of energy consumption, so as to determine the appropriate way to save energy, and even estimate the corresponding cost. It is of great significance to establish a suitable energy-saving scheme.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference27 articles.

1. A novel task scheduling in multiprocessor systems with genetic algorithm by using elitism stepping method;Rahmani;INFOCOMP J Comput Sci,2008

2. A heuristic tasks allocation algorithm;Raikwar;Int J Theor Appl Sci,2018

3. Heuristic based task scheduling in multiprocessor systems with genetic algorithm by choosing the eligible processor;Roy;Int J Distrib Parallel Syst (IJDPS),2012

4. Fault tolerant scheduling of hard real-time tasks on multiprocessor system using a hybrid genetic algorithm;Samal;Swarm Evol Comput,2014

5. Heuristic model for task allocation in distributed computer systems;Sarje;IEEE Proc Eng Comput Digit Tech,1991

Cited by 4 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