Artificial Neural Networks Model for Predicting Density and Compressive Strength of Concrete Cement paste

سال انتشار: 1384
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,605

فایل این مقاله در 8 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:

NCCE02_1072

تاریخ نمایه سازی: 27 مهر 1384

چکیده مقاله:

An artificial neural network of the feed-forward back-propagation type has been applied for predicting density and compressive strength properties of cement paste portion of concrete mixtures. Artificial neural networks (ANNs) have recently been introduced as an efficient artificial intelligence modeling technique for applications incorporating a large number of variables. Mechanical properties of concrete are highly influenced by density and compressive strength of concrete cement paste. Density and compressive strength of concrete cement paste are affected by several parameters, viz. water-cementitious materials ratio, silica fume unit contents, percentage of super-plasticizer, curing, cement type and etc. The 28-day compressive strength and saturated surface dry (SSD) density values are considered as the aim of the prediction. A total of 600 specimens were selected. The system was trained based on 350 training pairs chosen randomly from the data set, and tested using remaining 250 examples. Results indicate that density and compressive strength of concrete cement paste can be predicted much more accurately using ANN method compared to conventional models (Traditional regression analysis, statistical methods and etc.).

نویسندگان

Ehsan Rasa

BSc. Student of Civil engineering

Hamed Ketabchi

BSc. Student of Civil engineering

Mohammad Hadi Afshar

Associate Professor of Civil engineering Department

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 :
  • Neville A.M. and Brooks, J.J. "Concrete Technology", Longman Scientific & ...
  • Neville A.M. "Properties of Concrete", Longman Scientific & Technical, 1995. ...
  • Zong, Guang and Yun, 1999. "The Application of Acquisition of ...
  • Guang and Zong, 2000. "Prediction of Compressive Strength of Concrete ...
  • Lai and Serra, 1997. "Concrete Strength Prediction by Means of ...
  • Yeh, 1998. "Modeling of Strength of High Performance Concrete Using ...
  • Dias and Pooliyadda, 2001. "Neural Networks for Predicting Properties of ...
  • M.Nehdi, H.El Chabib and M.H.El Naggar, 2001. "Predicting Performance of ...
  • S.Haykin, 1994. "Neural Networks: _ C omprehensive Foundation, _ MacMillan, ...
  • Ju-Won Oh, In-Won Lee, Ju-Tae Kim and Jyu-Won Lee, 1999. ...
  • M.Nehdi, Y.Djebbar and A.Khan, 2001. "Neural Network Model for Cellular ...
  • Dave Anderson and George McNeill, 1992. "Artificial Neural Networks Technology, ...
  • Neural Network Modeling, "Qnet 2000 software", Vesta Services, Inc.Winnetka, IL. ...
  • نمایش کامل مراجع