基于BP神经网络和灰色模型的旅游热点商品类型预测研究

Jianning Su, L. Han, Wenjin Yang
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引用次数: 0

摘要

为探索疫情后旅游商品的发展方向,通过对未来热门旅游商品类型的预测分析,结合地域文化,提出了一种后疫情时代旅游商品的新设计载体。首先,利用网络爬虫收集热点产品数据,选取某一产品类型的销售指数、搜索指数和供应指数建立BP神经网络模型;然后,通过灰色模型预测后续搜索指数和供应指数,并通过BP模型预测该产品的销售数据。通过对预测销售数据与往年同期销售数据的对比分析,根据实际情况得出最畅销的旅游商品类型,然后结合城集地域文化进行旅游商品设计。通过对热门产品销售数据的预测,为后疫情时代的旅游商品行业提供了更丰富的行业信息,同时也为旅游行业开发新产品提出了新的方向。
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Research on forecasting hot tourism commodity types based on BP neural network and Grey model
In order to explore the development direction of tourism commodities after the epidemic, a new design carrier for tourism commodities in the post epidemic era was proposed by predicting and analyzing the types of hot tourist commodities in the future and combining with regional culture. Firstly, the hot product data is collected by web crawler, and the sales index, search index and supply index of a certain product type are selected to establish BP neural network model. Then, the subsequent search index and supply index are predicted by grey model, and the sales data of such products are predicted by BP model. Through the comparative analysis of the predicted sales data and the sales data of the same period in previous years, the best-selling tourism commodity types are obtained according to the actual situation, and then the tourism commodity design is carried out combined with Chengji regional culture. By predicting the sales data of hot products, it provides richer industry information for the tourism commodity industry in the post-epidemic era, and at the same time proposes a new direction for the tourism industry to develop new products.
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