The prediction analysis of compressive strength and electrical resistivity of environmentally friendly concrete incorporating natural zeolite using artificial neural network-Reference-Cited by-同舟云学术

The prediction analysis of compressive strength and electrical resistivity of environmentally friendly concrete incorporating natural zeolite using artificial neural network

Published:2022-01 Issue: Volume:317 Page:125876
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Shahmansouri Amir Ali,Yazdani Maziar,Hosseini Mehdi,Akbarzadeh Bengar Habib,Farrokh Ghatte Hamid

Publisher

Elsevier BV

Subject

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

Reference101 articles.

1. Enhancing evacuation response to extreme weather disasters using public transportation systems: a novel simheuristic approach;Yazdani;J. Comput. Des. Eng.,2020

2. Production scheduling of off-site prefabricated construction components considering sequence dependent due dates;Yazdani;Environ. Sci. Pollut. Res.,2021

3. Improving construction and demolition waste collection service in an urban area using a simheuristic approach: A case study in Sydney;Yazdani;Australia, Journal of Cleaner Production,2021

4. A Synthesis of Express Analytic Hierarchy Process (EAHP) and Partial Least Squares-Structural Equations Modeling (PLS-SEM) for Sustainable Construction and Demolition Waste Management Assessment: The Case of Malaysia;Ghafourian;Transportation Research Interdisciplinary Perspectives,2021

5. A novel machine learning approach combined with optimization models for eco-efficiency evaluation;Mirmozaffari;Applied Sciences,2020

Cited by 47 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Assessing the compressive strength of eco-friendly concrete made with rice husk ash: A hybrid artificial intelligence-aided technique;Structures;2024-10

2. Improving the experience of machine learning in compressive strength prediction of industrial concrete considering mixing proportions, engineered ratios and atmospheric features;Construction and Building Materials;2024-09

3. Predicting the mechanical properties of plastic concrete: An optimization method by using genetic programming and ensemble learners;Case Studies in Construction Materials;2024-07

4. Durability, mechanical, workability, and environmental assessment of self-consolidating concrete containing blast furnace slag and natural zeolite;Journal of Building Engineering;2024-06

5. An interpretable probabilistic machine learning model for forecasting compressive strength of oil palm shell-based lightweight aggregate concrete containing fly ash or silica fume;Construction and Building Materials;2024-05