Clockwork Recurrent Neural Network- M5T: A New Machine Learning Model for Predicting Reservoir Inflow

صفحه 297-310

Elham Ghanbari-Adivi، Hamid Hosseinkhani

• مشاهده مقاله
• اصل مقاله 646.73 K

A Machine Learning Framework for Predicting Maximum Displacement of Reinforced Masonry Shear Walls under Lateral Loading

صفحه 311-324

Shoaib Mansouri، Seyed Hadi Rashedi، Alireza Rahai

• مشاهده مقاله
• اصل مقاله 1 M

Enhancing Construction Sustainability through the Use of Recycled Aggregates in Concrete Production

صفحه 325-336

Mehrdad Khoshoei، Khalegh Barati

• مشاهده مقاله
• اصل مقاله 711.44 K

The behavior of high-strength LC3 concrete reinforced with recycled steel fiber under uniaxial compression and splitting tensile

صفحه 337-356

Saeed Sedighi، Alireza Rahai، Faramarz Moodi

• مشاهده مقاله
• اصل مقاله 1.86 M

Ductility-based strength reduction factor for pulse-like and non-pulse-like ground motions

صفحه 357-378

Seyyed Ebrahim Motallebi، Mehdi Poursha

• مشاهده مقاله
• اصل مقاله 3.2 M

Influence of Multi-Directional Expanded Metal Mesh Reinforcement on Cement Mortar Flexural Performance

صفحه 379-388

Shubbar Jawad Kadhim

• مشاهده مقاله
• اصل مقاله 881.83 K