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Application of Swarm Based Approaches for Elastic Modulus Prediction of Recycled Aggregate Concrete

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Advances in Swarm Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1054))

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Abstract

In concrete, the elastic modulus plays a vital role as a design parameter. Most of the empirical formulas used to predict the elastic modulus are limited to natural aggregate concretes (NAC). The formulae developed for recycled aggregate concrete (RAC) are constrained by experimental conditions since there is a considerable variation in recycled aggregate properties from place to place. In the present study, swarm based soft computing technique is used to overcome this issue. Artificial Neural Network (ANN) is trained by both standalone Levenberg-Marquardt back-propagation (LM-BP) technique and a hybrid of LM-BP and elephant herding optimization (EHO). The developed model is trained by 400 datasets obtained from literature which include seven inputs (i.e., water to cement (w/c) ratio, replacement of NA by RA in volume (r), coarse aggregates to cement (CA/C) ratio, fine aggregate to total aggregate (FA/TA) ratio, saturated surface dry specific gravity (SGSSD) of mixed CA(NA + RA), water absorption (\(W_a\)) of mixed CA and cube compressive strength (\(F_c\))) and one output as elastic modulus of RAC. The performances of the developed models are evaluated using standard statistical measures like MSE, r and MAE. The developed hybrid model yields ’r’ of 0.9966 and 0.9935, MSE of 0.4765 and 0.4807, and MAE of 1.1080 and 1.1888 for training and testing respectively which outperformed standalone technique of LM-BP in every aspect for predicting the elastic modulus of RAC. This shows that the hybrid model can be used effectively to predict the elastic modulus of RAC.

The authors thank NIT Goa and NIT Silchar.

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Acknowledgements

The authors are grateful to the Director, National Institute of Technology Goa, India; Director, National Institute of Technology Silchar, India for the support and encouragement provided by them and for permission to publish.

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Correspondence to Harish Narayana .

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Narayana, H., Janardhan, P. (2023). Application of Swarm Based Approaches for Elastic Modulus Prediction of Recycled Aggregate Concrete. In: Biswas, A., Kalayci, C.B., Mirjalili, S. (eds) Advances in Swarm Intelligence. Studies in Computational Intelligence, vol 1054. Springer, Cham. https://doi.org/10.1007/978-3-031-09835-2_8

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