现代电子技术2024，Vol.47Issue(2)：171-175,5.DOI:10.16652/j.issn.1004-373x.2024.02.031
融合随机统计规律与优化思想的成分数据预测方法研究
Research on compositional data prediction method integrating random statistical laws and optimization ideas
摘要
Abstract
Frequency distribution series prediction is an important class of problems in compositional data research.By integrating the statistical regularity of frequency distribution and optimization idea,the prediction method combining grey prediction theory and optimization method are used to construct the mathematical prediction model for quadratic programming by taking the minimization of the difference between the predicted values of expectation and mean as the goal,and setting the combination of historical experience constraints and constituent data constraints as the constraints.The empirical analysis of the frequency distribution structure data of core competencies among students in a certain major are used to verify the the effectiveness of the proposed prediction model.The results show that the average absolute error of the proposed prediction model is 0.0416,the root mean square error is 0.0460,and the directional cosine is 0.9824.In comparison with the spherical coordinate transformation prediction results,the proposed model has better prediction accuracy and is feasible.The research results show that the proposed prediction model has better prediction accuracy and can effectively solve the problem of frequency distribution sequence prediction,and meanwhile it can provide a new research idea for the prediction problem of compositional data containing 0 or 1 in the compositional data.关键词
成分数据/随机统计/频率分布/灰色预测模型/数学预测模型/专业核心能力Key words
compositional data/random statistics/frequency distribution/grey prediction model/mathematical prediction models/professional core competencies分类
信息技术与安全科学引用本文复制引用
喻芳宇,高胜哲..融合随机统计规律与优化思想的成分数据预测方法研究[J].现代电子技术,2024,47(2):171-175,5.基金项目
辽宁省教育厅基本科研项目(面上项目)(LJKZ0732) （面上项目）
设施渔业教育部重点实验室资助(202321) （202321）
