Research on infant behavior feature classification based on GWO-ELM algorithm

Mingshen Xu; Xinyu Shi; Po Guan; Zhixue Zhu

doi:10.1117/12.3012230

21 December 2023 Research on infant behavior feature classification based on GWO-ELM algorithm

Mingshen Xu, Xinyu Shi, Po Guan, Zhixue Zhu

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129703Z (2023) https://doi.org/10.1117/12.3012230
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

Regarding the association between maternal mental and physical health and infant behavior, this paper proposes a method that integrates Grey Wolf Optimization (GWO) with Extreme Learning Machine (ELM) for the correlation and classification of infant behavioral features and maternal health indicators. Firstly, a dataset of maternal mental and physical health and infant behavioral features is established. Using the Random Forest method, physical and psychological indicators of the mother and their eight primary influencing factors are extracted from the dataset. Subsequently, the classification accuracy of infant behavior is used as the fitness function for the Grey Wolf algorithm. The GWO algorithm optimizes the kernel and regularization parameters of the ELM, which are then fed into the ELM to train the four key feature parameters of infant behavior. Finally, it is applied to the classification task of infant behavior. The results indicate that the classification method combining GWO and ELM has an accuracy of 86% and a precision of 91%. This outperforms traditional classification models such as XGBoost and GBDT in detection and classification. It also surpasses the performance of ELM optimized by traditional optimization algorithms like SSA and PSO, validating the feasibility and effectiveness of the proposed method.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mingshen Xu, Xinyu Shi, Po Guan, and Zhixue Zhu "Research on infant behavior feature classification based on GWO-ELM algorithm", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129703Z (21 December 2023); https://doi.org/10.1117/12.3012230

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available