A hybrid model based on convolution neural network and long short-term memory for qualitative assessment of permeable and porous concrete-Reference-Cited by-同舟云学术

A hybrid model based on convolution neural network and long short-term memory for qualitative assessment of permeable and porous concrete

Published:2023-12 Issue: Volume:19 Page:e02254
ISSN:2214-5095
Container-title:Case Studies in Construction Materials
language:en
Short-container-title:Case Studies in Construction Materials

Author:

Kumar Manish,Kumar Manish,Singh Shatakshi,Kim Sunggon,Anand Ashutosh,Pandey Shatrudhan,Hasnain S M Mozammil^ORCID,Ragab Adham E.,Deifalla Ahmed Farouk

Funder

King Saud University

Publisher

Elsevier BV

Subject

Materials Science (miscellaneous)

Reference32 articles.

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2. Mechanical and durability studies on high-volume fly-ash concrete;Kumar;Struct. Concr.,2021

3. Modeling the behaviour of chemical resistant concrete modified with fly ash under different Ph environments;HAYDAR;J. Duhok Univ.,2020

4. Carbonation depth model and carbonated acceleration rate of concrete under different environment;Liu;Cem. Concr. Compos.,2020

5. Experimental study on the compressive strength and shrinkage of concrete containing fly ash and ground granulated blast-furnace slag;Li;Struct. Concr.,2019

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