Prediction of Behaviour in Older Adults in Nursing Homes

Liling Zhao, Zhaomiao Gong

2025

Abstract

The prediction of behavior in people throughout their middle years and beyond is critical in gerocomium, however it has an issue with erroneous performance positioning. The typical Shortest path algorithm is unable to address the phase limit issue in gerocomium, and the result is insufficient. As a result, a Behavioral data-mining methods-based prediction of older adult behaviors in nursing homes is provided, and the prediction of older adult behaviors in nursing homes is assessed. To begin, the support vector machine theory is used to discover the influencing elements, and the indicators are split based on the prediction of behavior in people throughout their middle years and beyond's needs to decrease interference factors in the prediction of behavior in people throughout their middle years and beyond. The support vector machine theory is then used to create a Behavioral data-mining methods prediction of behavior in people throughout their middle years and beyond scheme, and the outcomes of the prediction of behavior in people throughout their middle years and beyond are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Behavioral data-mining methods outperforms the standard Shortest path algorithm in terms of prediction of behavior in people throughout their middle years and beyond accuracy and time of influencing variables.

Paper Citation

in Harvard Style

Zhao L. and Gong Z. (2025). Prediction of Behaviour in Older Adults in Nursing Homes. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 518-525. DOI: 10.5220/0013547900004664

in Bibtex Style

@conference{incoft25,
author={Liling Zhao and Zhaomiao Gong},
title={Prediction of Behaviour in Older Adults in Nursing Homes},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={518-525},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013547900004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Prediction of Behaviour in Older Adults in Nursing Homes
SN - 978-989-758-763-4
AU - Zhao L.
AU - Gong Z.
PY - 2025
SP - 518
EP - 525
DO - 10.5220/0013547900004664
PB - SciTePress