4.7 Article

A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete

期刊

CONSTRUCTION AND BUILDING MATERIALS
卷 180, 期 -, 页码 320-333

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2018.05.201

关键词

High-performance concrete; Data mining; Evolutionary optimization; Artificial neural network; Modified firefly algorithm

资金

  1. University of Melbourne
  2. ARC Training Centre for Advanced Manufacturing of Prefabricated Housing (CAMP.H) at the University of Melbourne

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The compressive and tensile strength of high-performance concrete (HPC) is a highly nonlinear function of its constituents. The significance of expert frameworks for predicting the compressive and tensile strength of HPC is greatly distinguished in material technology. This study aims to develop an expert system based on the artificial neural network (ANN) model in association with a modified firefly algorithm (MFA). The ANN model is constructed from experimental data while MFA is used to optimize a set of initial weights and biases of ANN to improve the accuracy of this artificial intelligence technique. The accuracy of the proposed expert system is validated by comparing obtained results with those from the literature. The result indicates that the MFA-ANN hybrid system can obtain a better prediction of the high-performance concrete properties. The MFA-ANN is also much faster at solving problems. Therefore, the proposed approach can provide an efficient and accurate tool to predict and design HPC. (C) 2018 Elsevier Ltd. All rights reserved.

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