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Article

A Bio-Inspired Adaptive Probability IVYPSO Algorithm with Adaptive Strategy for Backpropagation Neural Network Optimization in Predicting High-Performance Concrete Strength

1
School of Computer Science, Hubei University of Technology, Wuhan 430068, China
2
Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
3
Institute for Environmental Design and Engineering, University College London, London WC1H 0NN, UK
*
Author to whom correspondence should be addressed.
Biomimetics 2025, 10(8), 515; https://doi.org/10.3390/biomimetics10080515
Submission received: 17 June 2025 / Revised: 27 July 2025 / Accepted: 5 August 2025 / Published: 6 August 2025

Abstract

Accurately predicting the compressive strength of high-performance concrete (HPC) is critical for ensuring structural integrity and promoting sustainable construction practices. However, HPC exhibits highly complex, nonlinear, and multi-factorial interactions among its constituents (such as cement, aggregates, admixtures, and curing conditions), which pose significant challenges to conventional predictive models. Traditional approaches often fail to adequately capture these intricate relationships, resulting in limited prediction accuracy and poor generalization. Moreover, the high dimensionality and noisy nature of HPC mix data increase the risk of model overfitting and convergence to local optima during optimization. To address these challenges, this study proposes a novel bio-inspired hybrid optimization model, AP-IVYPSO-BP, which is specifically designed to handle the nonlinear and complex nature of HPC strength prediction. The model integrates the ivy algorithm (IVYA) with particle swarm optimization (PSO) and incorporates an adaptive probability strategy based on fitness improvement to dynamically balance global exploration and local exploitation. This design effectively mitigates common issues such as premature convergence, slow convergence speed, and weak robustness in traditional metaheuristic algorithms when applied to complex engineering data. The AP-IVYPSO is employed to optimize the weights and biases of a backpropagation neural network (BPNN), thereby enhancing its predictive accuracy and robustness. The model was trained and validated on a dataset comprising 1,030 HPC mix samples. Experimental results show that AP-IVYPSO-BP significantly outperforms traditional BPNN, PSO-BP, GA-BP, and IVY-BP models across multiple evaluation metrics. Specifically, it achieved an R2 of 0.9542, MAE of 3.0404, and RMSE of 3.7991 on the test set, demonstrating its high accuracy and reliability. These results confirm the potential of the proposed bio-inspired model in the prediction and optimization of concrete strength, offering practical value in civil engineering and materials design.
Keywords: bio-inspired optimization; high-performance concrete; adaptive probability strategy; ivy algorithm; particle swarm optimization; backpropagation neural network bio-inspired optimization; high-performance concrete; adaptive probability strategy; ivy algorithm; particle swarm optimization; backpropagation neural network

Share and Cite

MDPI and ACS Style

Zhang, K.; Li, X.; Zhang, S.; Zhang, S. A Bio-Inspired Adaptive Probability IVYPSO Algorithm with Adaptive Strategy for Backpropagation Neural Network Optimization in Predicting High-Performance Concrete Strength. Biomimetics 2025, 10, 515. https://doi.org/10.3390/biomimetics10080515

AMA Style

Zhang K, Li X, Zhang S, Zhang S. A Bio-Inspired Adaptive Probability IVYPSO Algorithm with Adaptive Strategy for Backpropagation Neural Network Optimization in Predicting High-Performance Concrete Strength. Biomimetics. 2025; 10(8):515. https://doi.org/10.3390/biomimetics10080515

Chicago/Turabian Style

Zhang, Kaifan, Xiangyu Li, Songsong Zhang, and Shuo Zhang. 2025. "A Bio-Inspired Adaptive Probability IVYPSO Algorithm with Adaptive Strategy for Backpropagation Neural Network Optimization in Predicting High-Performance Concrete Strength" Biomimetics 10, no. 8: 515. https://doi.org/10.3390/biomimetics10080515

APA Style

Zhang, K., Li, X., Zhang, S., & Zhang, S. (2025). A Bio-Inspired Adaptive Probability IVYPSO Algorithm with Adaptive Strategy for Backpropagation Neural Network Optimization in Predicting High-Performance Concrete Strength. Biomimetics, 10(8), 515. https://doi.org/10.3390/biomimetics10080515

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