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Retraction Note to: Artificial neural networks application to predict the compressive damage of lightweight geopolymer

The Original Article was published on 25 April 2012

Retraction Note: Neural Comput & Applic (2013) 23:507–518 https://doi.org/10.1007/s00521-012-0945-y

The Editor-in-Chief has retracted this article [1] because it significantly overlaps with a large number of articles that were under consideration at the same time, including [2, 3], and previously published articles, including [4,5,6]. Additionally, the article shows evidence of peer review manipulation. The authors have not responded to any correspondence regarding this retraction.

References

  1. Nazari A (2013) Artificial neural networks application to predict the compressive damage of lightweight geopolymer. Neural Comput Applic 23:507–518. https://doi.org/10.1007/s00521-012-0945-y

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  2. Nazari A (2013) RETRACTED ARTICLE: Fuzzy logic-based prediction of compressive strength of lightweight geopolymers. Neural Comput Applic 23:865–872. https://doi.org/10.1007/s00521-012-1009-z

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  3. Nazari A, Khalaj G (2012) Prediction compressive strength of lightweight geopolymers by ANFIS. Ceram Int 38(6):4501–4510. https://doi.org/10.1016/j.ceramint.2012.02.026

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  4. Nazari A (2013) RETRACTED ARTICLE: Artificial neural networks for prediction compressive strength of geopolymers with seeded waste ashes. Neural Comput Applic 23:391–402. https://doi.org/10.1007/s00521-012-0931-4

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  5. Nazari A (2013) RETRACTED ARTICLE: Utilizing ANFIS for prediction water absorption of lightweight geopolymers produced from waste materials. Neural Comput Applic 23:417–427. https://doi.org/10.1007/s00521-012-0934-1

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  6. Nazari A, Riahi S (2013) RETRACTED ARTICLE: Artificial neural networks to prediction total specific pore volume of geopolymers produced from waste ashes. Neural Comput Applic 22:719–729. https://doi.org/10.1007/s00521-011-0760-x

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Nazari, A. Retraction Note to: Artificial neural networks application to predict the compressive damage of lightweight geopolymer. Neural Comput & Applic 33, 12239 (2021). https://doi.org/10.1007/s00521-020-05660-6

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  • DOI: https://doi.org/10.1007/s00521-020-05660-6