The Impact of Random Forest and WOA Optimization Algorithm on Maternal and Infant Physical and Mental Health

Mothers play a crucial role in the lives of infants, providing essential nourishment, physical care, emotional support, and a sense of security. This paper first analyzes the relationship between maternal physical and psychological indicators and infant behavioral characteristics and sleep quality. Secondly, predictive models are built using maternal physical and psychological indicators as inputs to forecast infant behavioral features. Furthermore, an optimization model is established to determine the minimum cost of treating infants classified as “contradictory” and “quiet.” Finally, K-means clustering and random forest models are employed to rate and predict infant sleep quality. By analyzing the data, it is discovered that optimal treatment strategies can be adjusted, as infant sleep quality can reach excellence under various behavioral characteristics. This paper provides theoretical support for optimizing treatment strategies.