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A Deep Learning-Based Customer Forecasting Tool

机译:基于深度学习的客户预测工具

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In this study, we developed a deep learning-based customer forecasting tool to improve the management quality of decision making. The proposed approach extracted the relationship between the number of customers and leading factors of huge amount of historical data. The conducted leading factors provide innovative approaches to adjust the manage settings regarding the labor arrangement strategies. In particular, the Point of Sale (POS) data was collected. Deep Learning were utilized to execute significant sales analysis and produce reliable predictions that would become administrative tools, especially with the building of a forecasting model based on customer behavior with weather as the prediction parameter. As a result of the information obtained by this research, recommendations concerning the pharmacy's administration were made, understanding the usefulness of basing the study on the customers. The deep learning-based customer forecasting tool can be used on different industries, which broadens the future work of this research.
机译:在这项研究中,我们开发了一种基于深度学习的客户预测工具,以提高决策的管理质量。所提出的方法提取了客户数量与大量历史数据的主导因素之间的关系。所进行的主导因素提供了创新的方法来调整有关劳务安排策略的管理设置。特别是,收集了销售点(POS)数据。深度学习被用于执行重要的销售分析并生成可靠的预测,这些预测将成为管理工具,尤其是在基于客户行为的预测模型的构建中,天气作为预测参数。从这项研究中获得的信息的结果,提出了有关药房管理的建议,并了解了将研究基于客户的有用性。基于深度学习的客户预测工具可用于不同行业,从而拓宽了本研究的未来工作。

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