福建电脑2025，Vol.41Issue(11)：37-41,5.DOI:10.16707/j.cnki.fjpc.2025.11.007
面向智慧矿山数据分析方案的设计与研究
Design and Research of Data Analysis Scheme for Intelligent Mine
摘要
Abstract
To solve the problem of processing massive data in mines,this paper proposes a dimensionality reduction and reconstruction scheme that integrates incremental principal component analysis(PCA)and neural networks.By constructing a dynamic PCA optimization model to achieve data dimensionality reduction,and training the neural network for prediction with a threshold of 0.005 mean square error.The experimental results show that the reconstruction mean square error is 0.0048,the prediction determination coefficient R ² is 0.9316,the average absolute percentage error is 0.41%,and all indicators meet the industrial grade standards.关键词
智慧矿山/增量主成分分析/神经网络/数据降维Key words
Smart Mine/IPCA/Neural Network/Data Dimensionality Reduction分类
信息技术与安全科学引用本文复制引用
周健文,闵玄,王嘉铭,杨雪,芮雪..面向智慧矿山数据分析方案的设计与研究[J].福建电脑,2025,41(11):37-41,5.基金项目
本文得到江苏省高等学校大学生创新创业训练项目《面向智慧矿山的环境监测预警系统研究与分析》(No.202513988019Y)资助. （No.202513988019Y）
