![](/images/graphics-bg.png)
Research on Optimization of Big Data Construction Engineering Quality Management Based on RNN-LSTM
Joint Authors
Fu, Hanliang
Wang, Daopeng
Fan, Jifei
Zhang, Bing
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-05
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Construction industry is the largest data industry, but with the lowest degree of datamation.
With the development and maturity of BIM information integration technology, this backward situation will be completely changed.
Different business data from a construction phase and operation and a maintenance phase will be collected to add value to the data.
As the BIM information integration technology matures, different business data from the design phase to the construction phase are integrated.
Because BIM integrates massive, repeated, and unordered feature text data, we first use integrated BIM data as a basis to perform data cleansing and text segmentation on text big data, making the integrated data a “clean and orderly” valuable data.
Then, with the aid of word cloud visualization and cluster analysis, the associations between data structures are tapped, and the integrated unstructured data is converted into structured data.
Finally, the RNN-LSTM network was used to predict the quality problems of steel bars, formworks, concrete, cast-in-place structures, and masonry in the construction project and to pinpoint the occurrence of quality problems in the implementation of the project.
Through the example verification, the algorithm proposed in this paper can effectively reduce the incidence of construction project quality problems, and it has a promotion.
And it is of great practical significance to improving quality management of construction projects and provides new ideas and methods for future research on the construction project quality problem.
American Psychological Association (APA)
Wang, Daopeng& Fan, Jifei& Fu, Hanliang& Zhang, Bing. 2018. Research on Optimization of Big Data Construction Engineering Quality Management Based on RNN-LSTM. Complexity،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1136894
Modern Language Association (MLA)
Wang, Daopeng…[et al.]. Research on Optimization of Big Data Construction Engineering Quality Management Based on RNN-LSTM. Complexity No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1136894
American Medical Association (AMA)
Wang, Daopeng& Fan, Jifei& Fu, Hanliang& Zhang, Bing. Research on Optimization of Big Data Construction Engineering Quality Management Based on RNN-LSTM. Complexity. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1136894
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136894