Firefly algorithm

Quantum mechanics

Expert system

Algorithm

Engineering

Materials science

Ultimate tensile strength

Set (abstract data type)

Particle swarm optimization

Computer science

Physics

Nonlinear system

Artificial intelligence

Composite material

Structural engineering

Programming language

Artificial neural network

Machine learning

Compressive strength

Construction and Building Materials

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.

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