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Intelligent Autofeedback and Safety Early-Warning for Underground Cavern Engineering during Construction Based on BP Neural Network and FEM
المؤلفون المشاركون
Lei, Xu
Zhang, Taijun
Ren, Qingwen
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-05-20
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
The low efficiency of feedback analysis is one of the main shortcomings in the construction of underground cavern engineering.
With this in mind, a method of intelligent autofeedback and safety early-warning for underground cavern is proposed based on BP neural network and FEM.
The training sample points are chosen by using uniform test design method, and the autogeneration of FEM calculation file for ABAQUS is realized by using the technique of file partition, information grouping, and orderly numbering.
Then, intelligent autoinversion of mechanics parameters is realized, and the automatic connection of parameter inversion, subsequent prediction, and safety early-warning is achieved.
The software of intelligent autofeedback and safety early-warning for underground cavern engineering during construction is developed.
Finally, the applicability of the proposed method and the developed software is verified through an application example of underground cavern of a pumped-storage power station located in Southwest China.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lei, Xu& Zhang, Taijun& Ren, Qingwen. 2015. Intelligent Autofeedback and Safety Early-Warning for Underground Cavern Engineering during Construction Based on BP Neural Network and FEM. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1074946
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lei, Xu…[et al.]. Intelligent Autofeedback and Safety Early-Warning for Underground Cavern Engineering during Construction Based on BP Neural Network and FEM. Mathematical Problems in Engineering No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1074946
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lei, Xu& Zhang, Taijun& Ren, Qingwen. Intelligent Autofeedback and Safety Early-Warning for Underground Cavern Engineering during Construction Based on BP Neural Network and FEM. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1074946
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1074946
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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