Comparison between Artificial Neural Network, Multi-variable Regression and Genetic Programming to Obtaining the Required Steel Ratio in Iranian Concrete Design Code

سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 625

فایل این مقاله در 21 صفحه با فرمت PDF قابل دریافت می باشد

این مقاله در بخشهای موضوعی زیر دسته بندی شده است:

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

DCEAEM02_240

تاریخ نمایه سازی: 30 بهمن 1394

چکیده مقاله:

The designs in most countries should be inevitably carried out by their native codes such as Iran. Since the Iranian concrete code does not exist in structural design software, most engineers in this country analyze the structures using commercial software but design the structural members manually. This point, motivated us to make a communication between Iranian code and some other well-known ones by several anticipate methods to determine the best method and also creating facility for the engineers.In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with both Iranian concrete codes (the differences between these two is described in detail later) which codes of America, Canada, Italy and New Zealand is chosen for a more special comparison with The Iranian ninth issue of national regulation for reasons that will discuss about. Different anticipate methods are used for comparing the codes: Artificial Neural Network (ANN), Multi-variable regression and Genetic Programming (GP) and results show that ANN performes more exactly than the others.

نویسندگان

Seyed Sadegh Naseralavi

Assistant Professor of Civil Engineering Department of Vali-e-Asr University of Rafsanjan

Najmeh Bemani

Master student of Civil Engineering Department of Vali-e-Asr University of Rafsanjan

Afshin Iranmanesh

Instrutor of Civil Engineering Department of Vali-e-Asr University of Rafsanjan

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله 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 مقاله لینک شده اند :
  • st National conference on development ...
  • of civil engineering , architecture _ electricity and mechanical in ...
  • of concrete _ _ ws _ _ _ _ computational ...
  • Paratipha Aggarwal, Yogeseh Aggarwal, Rafat Siddique, Sukshi Gupta, Harshid Garg, ...
  • R. Alizadeh, M. Chini, P. Ghods, M. Hoseini, N. Zobeiry, ...
  • نمایش کامل مراجع