TBM Advance Rate Prediction: An Artificial Neural Network Approach
Publish place: 3rd National Congress on Civil Engineering
Publish Year: 1386
نوع سند: مقاله کنفرانسی
زبان: English
View: 2,123
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
NCCE03_172
تاریخ نمایه سازی: 27 شهریور 1385
Abstract:
In tunneling, selection of a Tunnel Boring Machine (TBM) is based on the interaction between the rock characteristics and the features of the machine, which is being selected. TBM Advance Rate (TAR) against a particular rock as an economic factor plays a very important role on the selection of a TBM machine. Many factors relevant to the properties of rock, technical specification of TBM and working condition affect on the TBM advance rate. Many work carried out to predict TAR. In this paper an Artificial Neural network (ANN) modeling was adopted. The network used was a RBF, which showed promising results.
Keywords:
Authors
H. Mohammadi
MSc Student, Mining Engineering Department, Shahid Bahonar University of Kerman, Kerman, Iran
M. A. Ebrahimi Farsangi
Assistant Professor of Mining Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
R. Rahmannejad
Assistant Professor of Mining Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
H. Nezamabadi Poor
Assistant Professor of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, 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 :