基于综合控制方法的新型卷烟上市策略预测

IF 1.7 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Yu-Hua Mo, Chao Deng, Feijie Huang, Qian Tan, Yuan-Kun Li
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引用次数: 0

摘要

为了准确预测新产品卷烟营销策略的效果。我们以A省B市18个月的卷烟销售数据为研究样本,以新卷烟C为研究对象,采用随机森林方法对误差和缺失数据进行修正。然后,我们首先使用成熟卷烟品牌的短期历史销售数据和多标签系统,包括成熟卷烟品牌的历史销售数据、零售商销售数据、商人圈人群画像数据。基于各种机器学习方法,我们计算成熟香烟对新香烟的拟合权值,然后模拟和预测新香烟的销售趋势。应用效果检验发现,基于传统LSTM模型的新烟销量预测准确率仅为33.31%。相比之下,我们构建的新模型的预测精度可以达到94.17%。我们解决了新香烟销售预测遇到的局限性,填补了新香烟上市模型的研究空白。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting New Cigarette Launch Strategy based on Synthetic Control Method
In order to accurately predict the ef ect of new product cigarette marketing strategy.We take 18 months of cigarette sales data in city B of province A as the research sample, take new cigarette C as the researchobject, and use the random forest method to fix the errors and missing data. Then, we first use the mature cigarette brand's short-term historical sales and multiple labeling systems including the mature cigarette brand's historical sales data, retailer sales data, merchant circle crowd portrait data. Based on various machine learning method, we calculate the fitting weights of mature cigarettes to new cigarettes and thensimulate and predict the sales trend of new cigarettes. The application ef ect test found the accuracy of new cigarette sales prediction based on the traditional LSTM model was only 33.31%. In comparison, the prediction accuracy of the new model we constructed can reach 94.17%. We address the limitations encountered in new cigarette sales prediction, and fill the research gap in new cigarette launch models.
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
22
审稿时长
4 weeks
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