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Research on Optimization of Big Data Construction Engineering Quality Management Based on RNN-LSTM
المؤلفون المشاركون
Fu, Hanliang
Wang, Daopeng
Fan, Jifei
Zhang, Bing
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-07-05
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1136894
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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