Techno Press
You logged in as Techno Press

Computers and Concrete
  Volume 27, Number 5, May 2021, pages 489-512

Prediction of compressive strength of concrete modified with fly ash: Applications of neuro-swarm and neuro-imperialism models
Ahmed Mohammed, Rawaz Kurda, Danial Jahed Armaghani and Mahdi Hasanipanah

    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
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

Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2021 Techno Press
P.O. Box 33, Yuseong, Daejeon 305-600 Korea, Tel: +82-42-828-7996, Fax : +82-42-828-7997, Email: