{"title":"Energy consumption simulation of green building based on BIM system and improved neural network","authors":"Chenguang Liu","doi":"10.3233/JIFS-189802","DOIUrl":null,"url":null,"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.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"2006 1","pages":"1-12"},"PeriodicalIF":1.5000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-189802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 3
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.
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.