网络智能金融数据挖掘分析系统及定量模型研究

Yaling Chen, Zhengdong Hu
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引用次数: 0

摘要

本文基于时间序列数据挖掘,研究财务数据分析系统和定量模型,以提高财务数据的服务质量,提高财务数据的管理效率,为财务数据管理者提供更便捷的服务。在设计财务数据分析系统时,将系统划分为六大模块:数据采集与更新功能、财务咨询信息管理功能、财务风控管理功能、智能挖掘与分析功能、财务数据监控功能、股票相关性比较功能。其中,建立了智能挖掘过程中基于时间序列的数据挖掘风险控制模型。本文的金融数据预测方法采用了长、短时记忆算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Network Intelligent Finance Data Mining and Analysis System and Quantitative Model
Based on time series data mining, this paper studies financial data analysis systems and quantitative models to improve the service quality of financial data, improve the management efficiency of financial data, and provide financial data managers with more convenient services. When the financial data analysis system was designed, the system was divided into six modules: data collection and update function, financial consulting information management function, financial risk control management function, intelligent mining and analysis function, financial data monitoring function, and stock correlation comparison function. Among them, a data mining risk control model based on time series is established during intelligent mining. In this paper, the method of financial data prediction uses the long and short time memory algorithm.
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