Predicting stress-strain behavior of normal weight and lightweight aggregate concrete exposed to high temperature using LSTM recurrent neural network-Reference-Cited by-同舟云学术

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Predicting stress-strain behavior of normal weight and lightweight aggregate concrete exposed to high temperature using LSTM recurrent neural network

Published:2023-01 Issue: Volume:362 Page:129703
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Tanhadoust A.,Yang T.Y.,Dabbaghi F.,Chai H.K.,Mohseni M.,Emadi S.B.,Nasrollahpour S.

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference56 articles.

1. Mechanical performance of green concrete produced with untreated coal waste aggregates;Karimaei;Constr Build Mater.,2020

2. High-Temperature Behavior of Lightweight Aggregate Reinforced Concrete Beams;Dabbaghi;Materials Journal.,2022

3. Life cycle assessment multi-objective optimization and deep belief network model for sustainable lightweight aggregate concrete;Dabbaghi;J Clean Prod.,2021

4. Evaluation of fracture energy, toughness, brittleness, and fracture process zone properties for lightweight concrete exposed to high temperatures;Dabbaghi;Theoretical and Applied Fracture Mechanics.,2021

5. Characterizing fiber reinforced concrete incorporating zeolite and metakaolin as natural pozzolans;Dabbaghi;Structures.,2021

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4. Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms;Materials Today Communications;2024-08

5. Pruning Long Short-Term Memory: A Model for Predicting the Stress–Strain Relationship of Normal and Lightweight Aggregate Concrete at Finite Temperature;Fire Technology;2024-07-12

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