{"title":"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","authors":"Jianning Su, L. Han, Wenjin Yang","doi":"10.1109/ICIDDT52279.2020.00115","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":6781,"journal":{"name":"2020 International Conference on Innovation Design and Digital Technology (ICIDDT)","volume":"11 1","pages":"576-580"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on forecasting hot tourism commodity types based on BP neural network and Grey model\",\"authors\":\"Jianning Su, L. Han, Wenjin Yang\",\"doi\":\"10.1109/ICIDDT52279.2020.00115\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":6781,\"journal\":{\"name\":\"2020 International Conference on Innovation Design and Digital Technology (ICIDDT)\",\"volume\":\"11 1\",\"pages\":\"576-580\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Innovation Design and Digital Technology (ICIDDT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIDDT52279.2020.00115\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Innovation Design and Digital Technology (ICIDDT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIDDT52279.2020.00115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.