Retraction Note to: Artificial neural networks application to predict the compressive damage of lightweight geopolymer (Neural Computing and Applications, (2013), 23, 2, (507-518), 10.1007/s00521-012-0945-y);Artificial neural networks application to predict the compressive damage of lightweight geopolymer

Neural Computing and Applications

Volumn 23, Issue 2, 2013, Pages 507-518

  Nazari, Ali ^a  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

ANNs; Compressive strength; Fly ash; Geopolymer; Palm oil clinker; Rice husk bark ash

Indexed keywords

AGGREGATES; COMPRESSIVE STRENGTH; CURING; FEEDFORWARD NEURAL NETWORKS; FLY ASH; FORECASTING; GEOPOLYMERS; INORGANIC POLYMERS; MIXTURES; PALM OIL;

ANNS; GEOPOLYMER; LIGHTWEIGHT GEOPOLYMER; MULTILAYER FEEDFORWARD NEURAL NETWORKS; NEURAL NETWORKS APPLICATIONS; NEURAL NETWORKS MODEL; PALM OIL CLINKERS; RICE HUSK-BARK ASHES;

MULTILAYER NEURAL NETWORKS;

EID: 84880742750     PISSN: 09410643     EISSN: 14333058     Source Type: Journal    
DOI: 10.1007/s00521-020-05660-6     Document Type: Erratum

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