GDP波动与物流行业就业关系经济模型仿真

发布时间：2018-03-27 23:15

本文选题：物流行业　切入点：多元数据　出处：《计算机仿真》2014年12期

【摘要】：在经济发展中,随着经济总量GDP情况的不断变化,最为直接的物流行业就业人数会发生较大的波动,物流就业人员数量与GDP数据众多属性都有关联,探索两者的关系十分重要。GDP的波动与物流行业的关系呈现非线性变化,过多的关联和约束条件使得两者的整体关联极其复杂。传统的评估模型以单目标,多约束条件描述这种复杂关联,使得约束条件过多,无法控制建模中的残差,建模结果笼统,模型准确性不高。提出基于多元数据加权均值的GDP与物流就业关系分析模型。根据经济GDP数据与物流行业就业的数据采集时间进行划分,分析数据时域内分析结果残差与关系估计数据的关联性,考虑各种情况下,数据残差波动与关联性的误差比率,根据比率指导建立多元就业数据加权均值模型,通过抑制残差,实现GDP与物流行业就业关系的准确建模。实验结果表明,利用改进方法进行经济危机下GDP与物流行业就业促进之间关系的评估,能够提高评估准确性。
[Abstract]:In the economic development, with the constant change of the total GDP of the economy, the most direct employment in the logistics industry will fluctuate greatly. The number of the logistics employment is related to the many attributes of the GDP data. It is very important to explore the relationship between the two. The fluctuation of GDP and the relationship between logistics industry show nonlinear change, too much correlation and constraint conditions make the overall correlation between the two extremely complex. The multi-constraint conditions describe this kind of complex relation, which makes the constraints too many and can't control the residual in the modeling. The modeling results are general. The analysis model of the relationship between GDP and logistics employment based on multivariate data weighted mean is put forward. According to the economic GDP data and the data collection time of the logistics industry employment, the paper divides the data collection time of the economic GDP data and the logistics industry employment. When analyzing data, the relationship between residual and relational estimation data is analyzed. Considering the error ratio of data residual fluctuation and correlation, the weighted mean model of multivariate employment data is established according to the guidance of ratio, and the residual error is restrained. The experimental results show that using the improved method to evaluate the relationship between GDP and the employment promotion of logistics industry under the economic crisis can improve the accuracy of the evaluation.
【作者单位】：西北工业大学学生处;
【分类号】：F259.2;F124;TP391.9

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