Study on Dispatching Model of Block Economy Based-Data Mining

Xiaohan Gao, Qiang Lin
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Abstract

Economic dispatch plays the most important role in the economic and stability of financial system operation. With the introduction of many intelligent management models in economic construction, the scale of collectible financial system data has shown an explosive growth trend. In the paper, a PSO-LSSVM data mining prediction model based on big data is established, and a block-based economic dispatch method is proposed to deal with financial risks. In the experiment, financial data is used as a sample to predict the actual risk curve. The results show that the risk prediction result obtained by the proposed prediction algorithm is closer to the actual risk. The validity of the model is explained, and the experimental results provide a decision-making basis for the economic dispatch of the financial system.
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基于数据挖掘的块经济调度模型研究
经济调度对金融体系的经济稳定运行起着至关重要的作用。随着经济建设中诸多智能管理模式的引入,可收集金融系统数据规模呈现爆发式增长趋势。本文建立了基于大数据的PSO-LSSVM数据挖掘预测模型,提出了一种基于分块的经济调度方法来应对金融风险。在实验中,以金融数据为样本来预测实际的风险曲线。结果表明,本文提出的预测算法得到的风险预测结果更接近实际风险。说明了模型的有效性,实验结果为金融系统的经济调度提供了决策依据。
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