基于BIM系统和改进神经网络的绿色建筑能耗仿真

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS
Chenguang Liu
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引用次数: 3

摘要

建筑业是国民经济产业中不可缺少的重要支撑。建筑行业生产周期长、参与者多、类型多等特点,决定了建筑行业的发展无疑是非常困难的。为了实现建筑业的快速发展,转型是未来建筑业的必然发展方向,这需要科学技术的帮助。随着科学技术的发展,信息技术和大数据已经应用到各行各业,而这些也是支撑建筑行业转型的重要手段。要实现绿色发展,降低能耗是必然的措施。通过建立基于大数据的能耗监测平台,可以实现能耗分析和降低。BIM系统的应用是一种基于信息化的能耗分析方法。该技术可以实现对能耗的分析和预测,从而确定合适的节能方式,甚至估算出相应的成本。建立合适的节能方案具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy consumption simulation of green building based on BIM system and improved neural network
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.
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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