摘要
在信息化时代背景下,人们尤为关注如何从海量数据中提取信息、针对信息进行统计分析、辅助工作决策。随着固定资产投资在我国的迅速发展,固定资产投资数据对分析国家经济形势、预测未来投资具有愈发重要的意义。本文介绍了固定资产数据目前在我国的应用现状和数据挖掘技术应用于预测系统的现状,剖析和比较了数据挖掘的传统挖掘算法、基于机器学习和深度学习的挖掘算法,并指出未来发展趋势和数据挖掘面临的挑战和应对建议。
In the context of the information age,there is a growing focus on how to extract information from massive data sets,conduct statistical analyses,and support decision-making.With the rapid development of fixed asset investment in China,data on fixed asset investment has become increasingly important for analyzing the national economic situation and predicting future investments.This paper introduces the current application status of fixed asset investment data in China and the application status of data mining technologies in predictive systems.It analyzes and compares traditional data mining algorithms with algorithms based on machine learning and deep learning,and discusses future development trends as well as challenges and recommendations for data mining.
作者
郑瑜
Zheng Yu(National Information Center,Beijing 100045,China)
出处
《科学与信息化》
2025年第9期174-177,共4页
Technology and Information
