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1 Retraction Note to: Neural Comput & Applic (2019) 31 (Suppl 2):S733–S741 https://doi.org/10.1007/s00521-012-1082-3
The Editor-in-Chief has retracted this article [1] because it significantly overlaps with a number of articles including those that were under consideration at the same time [2, 3] and previously published articles [4,5,6]. Additionally, the article shows evidence of peer review manipulation. The authors have not responded to any correspondence regarding this retraction.
References
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Nazari A (2012) Application of fuzzy logic for prediction compressive strength of OPC based geopolymers. Mater Technol 27(5):364–370. https://doi.org/10.1179/1753555712Y.0000000021
Riahi S, Nazari A (2019) Predicting the effects of nanoparticles on early age compressive strength of ash-based geopolymers by artificial neural networks. Neural Comput Appl 31:743–750. https://doi.org/10.1007/s00521-012-1085-0
Nazari Ali (2013) Compressive strength of geopolymers produced by ordinary Portland cement: application of genetic programming for design. Mater Des 43:356–366. https://doi.org/10.1016/j.matdes.2012.07.012
Nazari A (2013) Artificial neural networks for prediction compressive strength of geopolymers with seeded waste ashes. Neural Comput Appl 23:391–402. https://doi.org/10.1007/s00521-012-0931-4
Nazari A (2013) Artificial neural networks application to predict the compressive damage of lightweight geopolymer. Neural Comput Appl 23:507–518. https://doi.org/10.1007/s00521-012-0945-y
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Nazari, A., Hajiallahyari, H., Rahimi, A. et al. Retraction Note to: Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks. Neural Comput & Applic 32, 15669 (2020). https://doi.org/10.1007/s00521-020-05121-0
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DOI: https://doi.org/10.1007/s00521-020-05121-0