Retraction
Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks
Paper Information
Record ID:
23669
Journal:
Publication Date:
July 26, 2012
Retraction Date:
June 18, 2020
(5.4 years years ago)
Subjects:
Institution:
Department of Materials Engineering, Saveh Branch, Islamic Azad University, Saveh, IranCountry:
š®š· IranArticle Type:
Publisher:
Springer
Open Access:
Yes
PubMed ID:
Not indexed in PubMed
Retraction PubMed ID:
Not indexed in PubMed
Retraction Details
Citations (19)
19
Total Citations9
Post-Retraction(47.4%)
7
Pre-Retraction1
Same DayPost-Retraction Citation Analysis
0
Within 30 days
4
Within 1 year
4
After 2+ years
1645
Days since retraction (latest)
Heavy Metals Removal Using Carbon Based Nanocomposites
Unknown Authors
Unknown Journal
Published: Unknown
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Unknown
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Dec 2024
1645 days after retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: May 2024
1419 days after retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Apr 2024
1403 days after retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Feb 2023
981 days after retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Jul 2021
378 days after retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Mar 2021
256 days after retraction
Retraction Note to: ANN model to predict the effects of composition and heat treatment parameters on transformation start temperature of microalloyed steels
Gholamreza Khalaj, Ali Nazari, H. Yoozbashizadeh et al. (5 authors)
Neural Computing and Applications
Published: Jan 2021
215 days after retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Nov 2020
136 days after retraction
Retraction Note to: Artificial neural networks for prediction Charpy impact energy of Al6061/SiCp-laminated nanocomposites
Ali Nazari, Vahid Reza Abdinejad
Neural Computing and Applications
Open Access
Published: Oct 2020
113 days after retraction
Retraction Note to: Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks
Ali Nazari, Hadi Hajiallahyari, Ali Rahimi et al. (5 authors)
Neural Computing and Applications
Open Access
Published: Jun 2020
Same day as retraction
Retraction Note to: Predicting the effects of nanoparticles on early age compressive strength of ash-based geopolymers by artificial neural networks
Shadi Riahi, Ali Nazari
Neural Computing and Applications
Open Access
Published: Jun 2020
3 days before retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: May 2020
43 days before retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Apr 2020
78 days before retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Feb 2020
121 days before retraction
Prediction of fresh and hardened properties of self-compacting concrete using support vector regression approach
Prasenjit Saha, Prasenjit Debnath, Paul Thomas
Neural Computing and Applications
Published: Jun 2019
125 citations
125 citations
370 days before retraction
Paper citing Prediction compressive strength of Portland cement...
Unknown Authors
Unknown Journal
Published: Nov 2017
948 days before retraction
Predicting compressive strength of different geopolymers by artificial neural networks
Ali Nazari, F. PachecoāTorgal
Ceramics International
Open Access
Published: Sep 2012
61 citations
61 citations
2847 days before retraction
Quick Stats
Total Citations:
19
Years Since Retraction:
5.4 years
Open Access:
Yes
Last Checked:
Jul 24, 2025