Optimization of complex maternal and child behavior characteristics based on multivariatecorrelation and optimization algorithms
基于多元相关及优化算法的复杂母婴行为特征优化

摘要

该论文深入探究了母亲的身体指标与心理指标和婴儿行为特征之间的复杂关系，并进一步提出了具有创新性的数学建模方法来预测和解析这些关联。论文的研究方法严谨，首先进行了数据预处理，以确保数据的准确性和可用性，然后通过统计分析技术，精准地揭示了母亲健康状况与婴儿行为特征之间的内在联系。在这个过程中，聚类技术被有效应用，帮助研究者在复杂的数据中找出具有相似特性的群组，进一步加深了我们对母亲和婴儿关系的理解。该论文成功地构建了优化模型，这一模型旨在减少治疗矛盾型婴儿行为特征的成本。这不仅提供了一个全新的视角来看待婴儿行为特征的问题，也为实现向中等型与安静型的转变提供了经济可行的策略。

Abstract

The paper deeply explores the complex relationship between maternal physical and psychological indicators and infant behavioral characteristics, and further proposes innovative mathematical modeling methods to predict and analyze these associations. The research method of the paper is rigorous. First, data preprocessing is conducted to ensure the accuracy and usability of the data. Then, through statistical analysis techniques, the intrinsic relationship between maternal health status and infant behavioral characteristics is accurately revealed. In this process, clustering technology is effectively applied to help researchers identify groups with similar characteristics in complex data, further deepening our understanding of the relationship between mothers and infants.This paper successfully constructed an optimization model, which aims to reduce the cost of treating contradictory infant behavior characteristics. This not only provides a new perspective on the issue of infant behavioral characteristics, but also provides economically feasible strategies for achieving a shift towards intermediate and quiet types.