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METHODS AND SYSTEMS FOR TRANSFORMING LOGISTIC VARIABLES INTO NUMERICAL VALUES FOR USE IN DEMAND CHAIN FORECASTING

机译:将逻辑变量转换为数值链以供需求链预测中使用的方法和系统

摘要

An improved method for forecasting and modeling product demand. The forecasting methodology employs a multivariable regression model to model the causal relationship between product demand and the attributes of past promotional activities. This improved forecasting methodology enhances the applicability of regression models when dealing with logistic variables. It provides a novel technique to transform such variables into numerical values, resulting in more accurate and more efficient regression models. Furthermore, the reduction in the number of variables improves the stability and predictive power of the regression models.
机译:一种预测和建模产品需求的改进方法。预测方法采用多变量回归模型来建模产品需求与过去促销活动的属性之间的因果关系。在处理逻辑变量时,这种改进的预测方法提高了回归模型的适用性。它提供了一种新颖的技术将这些变量转换为数值,从而产生更准确,更有效的回归模型。此外,变量数量的减少提高了回归模型的稳定性和预测能力。

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