Article: Health management of young and middle-aged residents based on probabilistic optimisation BP neural network Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.14 pp.87 - 103 Abstract: The health status of the young and middle-aged population has a significant impact on the stable functioning of society. To address the issue of poor prediction accuracy in the current study, the BP neural network (BPNN) is first improved based on Bayesian optimisation (BO), and the parameter combination that maximises the conditional probability is selected to improve the fitting accuracy of the model. Then the factors affecting the health status are analysed, the influencing factors are decomposed and reconstructed using the improved variational modal decomposition (VMD) and fuzzy entropy algorithm, and the objective function is iteratively searched through BO probability theory to obtain the degree of the BPNN parameter that minimises the prediction error. Finally, corresponding health management suggestions are proposed for the prediction results. The simulation results indicate that the accuracy of the proposed method is 95.37%, which significantly improves the prediction accuracy. Inderscience Publishers - linking academia, business and industry through research

Title: Health management of young and middle-aged residents based on probabilistic optimisation BP neural network

Authors: Yuanyuan Wen

Addresses: College of Computer Science and Engineering, Taizhou Institute of Science and Technology, NJUST, Taizhou, 225300, China

Abstract: The health status of the young and middle-aged population has a significant impact on the stable functioning of society. To address the issue of poor prediction accuracy in the current study, the BP neural network (BPNN) is first improved based on Bayesian optimisation (BO), and the parameter combination that maximises the conditional probability is selected to improve the fitting accuracy of the model. Then the factors affecting the health status are analysed, the influencing factors are decomposed and reconstructed using the improved variational modal decomposition (VMD) and fuzzy entropy algorithm, and the objective function is iteratively searched through BO probability theory to obtain the degree of the BPNN parameter that minimises the prediction error. Finally, corresponding health management suggestions are proposed for the prediction results. The simulation results indicate that the accuracy of the proposed method is 95.37%, which significantly improves the prediction accuracy.

Keywords: health prediction; Bayesian optimisation; probability theory; BP neural network; BPNN; variational modal decomposition; VMD.

DOI: 10.1504/IJICT.2025.146366

International Journal of Information and Communication Technology, 2025 Vol.26 No.14, pp.87 - 103

Received: 27 Mar 2025
Accepted: 10 Apr 2025
Published online: 27 May 2025 *

Title: Health management of young and middle-aged residents based on probabilistic optimisation BP neural network

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