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一个基于变压器的框架,用于企业销售预测
1School of Accounting, Yunnan University of Finance and Economics, Yunnan, China.
PeerJ. Computer science
|December 9, 2024
概括
本研究介绍了一种新的基于变压器的商业销售预测框架,其性能优于传统的机器学习模型. 这种先进的模型提高了低维表格数据的预测准确度,有助于战略业务决策.
科学领域:
- 业务分析 业务分析
- 机器学习 机器学习
- 深度学习 (Deep Learning) 是一种深度学习.
背景情况:
- 销售预测对于业务运营至关重要,影响库存,资源配置和财务规划.
- 准确的销售预测对于优化现金流,调整策略和战略规划至关重要.
研究的目的:
- 展示使用变压器进行业务销售预测的计算框架.
- 为低维的表格数据量身定制变压器模型.
主要方法:
- 开发了一个使用变压器深度学习架构的新型计算框架.
- 专门为低维的表格数据集设计模型.
主要成果:
- 拟议的变压器模型显著超过了传统的机器学习模型.
- 实现了降低平均绝对误差 (MAE),平均平方误差 (MSE) 和根平均平方误差 (RMSE).
- 达到了高的R平方值,接近0.95,表明更高的预测准确度.
结论:
- 基于变压器的模型是有效的销售预测低维的表格数据.
- 该模型的准确性和稳定性为增强业务决策提供了有价值的工具.
- 适用于各种涉及低维表格数据分析的研究.
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