Novel hybrid informational model for predicting the creep and shrinkage deflection of reinforced concrete beams containing GGBFS

Novel hybrid informational model for predicting the creep and shrinkage deflection of reinforced concrete beams containing GGBFS

<p>This study investigates a Novel Hybrid Informational model for the prediction of creep and shrinkage deflection of reinforced concrete (RC) beams containing different percentages of ground granulated blast furnace slag (GGBFS) at different ages, varying from 1 to 150 days. The percentage of...

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Bibliographic Details
Main Author: Iman Faridmehr (14150616) (author)
Other Authors: Mohd Shariq (456621) (author), Vagelis Plevris (14158863) (author), Nasrin Aalimahmoody (14150622) (author)
Published: 2022
Subjects:
Artificial intelligence
Software engineering
Artificial Intelligence
Software
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