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Computers and Concrete Volume 27, Number 5, May 2021 , pages 489-512 DOI: https://doi.org/10.12989/cac.2021.27.5.489 |
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Prediction of compressive strength of concrete modified with fly ash: Applications of neuro-swarm and neuro-imperialism models |
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Ahmed Mohammed, Rawaz Kurda, Danial Jahed Armaghani and Mahdi Hasanipanah
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| Abstract | ||
| In this study, two powerful techniques, namely particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) were selected and combined with a pre-developed ANN model aiming at improving its performance prediction of the compressive strength of concrete modified with fly ash. To achieve this study's aims, a comprehensive database with 379 data samples was collected from the available literature. The output of the database is the compressive strength (CS) of concrete samples, which are influenced by 9 parameters as model inputs, namely those related to mix composition. The modeling steps related to ICA-ANN (or neuro-imperialism) and PSO-ANN (or neuro-swarm) were conducted through the use of several parametric studies to design the most influential parameters on these hybrid models. A comparison of the CS values predicted by hybrid intelligence techniques with the experimental CS values confirmed that the neuro-swarm model could provide a higher degree of accuracy than another proposed hybrid model (i.e., neuro-imperialism). The train and test correlation coefficient values of (0.9042 and 0.9137) and (0.8383 and 0.8777) for neuro-swarm and neuro-imperialism models, respectively revealed that although both techniques are capable enough in prediction tasks, the developed neuro-swarm model can be considered as a better alternative technique in mapping the concrete strength behavior. | ||
| Key Words | ||
| artificial neural networks; fly ash; compressive strength; statistical analysis; intelligent computing | ||
| Address | ||
| Ahmed Mohammed: College of Engineering, Civil Engineering Department, University of Sulaimani, Kurdistan Region, Iraq Rawaz Kurda: Department of Highway Engineering Techniques, Technical Engineering College, Erbil Polytechnic University, Erbil, Kurdistan-Region, Iraq; CERIS, Civil Engineering, Architecture, and Georresources Department, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001, Lisbon, Portugal Danial Jahed Armaghani: Department of Urban Planning, Engineering Networks and Systems, Institute of Architecture and Construction, South Ural State University, 76, Lenin Prospect, Chelyabinsk 454080, Russia Mahdi Hasanipanah: Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam | ||