Estimation of Groundwater Seepage Risks into Tunnel Using Radial Basis Function Networks
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: Persian
View: 134
This Paper With 16 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JISE-45-2_008
تاریخ نمایه سازی: 29 شهریور 1401
Abstract:
In this study, Site Groundwater Rating (SGR) in the Amirkabir tunnel has been estimated using Radial Basis Function Networks (RBFNs). SGR is the first rating method that by considering the parameters like joint frequency, joint aperture, schistosity, crashed zones, karstification, soil permeability coefficient, tunnel location in the water table or piezometric surface, and the amount and intensity of annual raining in the area, classifies the tunnel path from the risk of groundwater seepage point of view. In this article, using an RBFN, an estimation of SGR along the Amirkabir tunnel path was performed. Field data obtained from primary studies in the tunnel was used to train and test the prepared network. For the testing set, modeling results showed that SGR could be predicted with the mean error of ۳.۵۷% and ۴.۷۶% using radial basis network and exact radial basis network functions, respectively. A High correlation between the SGR of the tunnel path and the network answers, confirmed the prepared RBFN.
Keywords:
Authors
Hadi Farhadian
Department of Mining Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran.
Seyed Ahmad Eslaminezhad
Department of surveying and Geomatics Engineering, College of Engineering, University of Tehran, Tehran, Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :