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A New Algorithm about Market Demand Prediction of Automobile

机译:汽车市场需求预测的新算法

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An extensive evaluation hierarchy model of automobile short-term demand was established to prevent thedisadvantages of previous models mainly for single time series. The definition of extensive correlationevaluation was proposed, and then the method was discussed to reflect the correlation of factors on automobiledemand. Utilizing extensive skills, factors and sub-factors were represented as correlation eigenmatrix whichcould ensure the level of each factor’s influences on automobile demand. Then short-term historical data waspredicted while it was compared with existing data, the results show that the predictive error is less than 6%,which confirms the validation of predictive model. This study provides the foundations for government’smacroeconomic control and automobile manufacturers’ production.
机译:建立了广泛的汽车短期需求评估层次模型,以防止以前模型主要针对单个时间序列的缺点。提出了广义相关性评价的定义,然后讨论了反映汽车需求因素相关性的方法。利用广泛的技能,将因子和子因子表示为相关特征矩阵,可以确保每个因子对汽车需求的影响程度。然后将其与现有数据进行比较,对短期历史数据进行预测,结果表明预测误差小于6%,证实了预测模型的有效性。该研究为政府宏观经济调控和汽车制造商的生产提供了基础。

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