Prediction of Rural Tourist number in Guangdong Province Based on Prophet-LSTM in the Context of Blockchain

Linlin Sun; Jieru Xie; Yangcheng Tang; Wei Chen; Danci Wang; Jiawen Li

doi:10.54691/bcpbm.v21i.1183

Authors

Linlin Sun
Jieru Xie
Yangcheng Tang
Wei Chen
Danci Wang
Jiawen Li

DOI:

https://doi.org/10.54691/bcpbm.v21i.1183

Keywords:

Rural tourists, Blockchain, VAR model, Prophet-LSTM time series

Abstract

Guangdong, as a province with large population and economy, has huge tourists market demand. The paper predicts people's preference for the development of "blockchain + rural tourists" under blockchain technology, and then applies the characteristics of blockchain itself to rural tourists in a more targeted way. The paper establishes a vector autoregressive VAR model and a Prophet-LSTM-based prediction model for the number of tourists based on the data of tourist reception in Guangdong Province from April 2000 to November 2020. The VAR model is used to empirically prove the impact of blockchain background on the number of rural tourists; a combined Prophet-LSTM-based prediction model is established to forecast the number of rural tourists in the next two years. The results show that blockchain technology has influenced the number of rural tourists in Guangdong Province to a certain extent; n addition, in the market in the next two years, the number of travelers will show a fluctuating upward trend, for which the demand will continue to expand, and blockchain + rural tourists has market potential.

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References

Li Li, Lu Chaojin. The current situation of blockchain industry layout and development suggestions in Guangdong Province [J]. Guangdong Science and Technology,2020,29(7):17-19.

Li Chun, Cao Yanjiao, Lv Benfu. Research on the prediction of tourists' number based on web search index--Xinjiang Altay ice and snow tourists as an example[J]. Xinjiang Social Science, 2016(06): 46-51.

Liang Zongjing, Kuang Yun. Research on prediction of autoregressive distribution lag model of tourists demand based on search big data [J]. Productivity Research,2018(02):15-22.

Li Yue. Prediction of tourists number based on ARIMA model[D]. Jiangxi University of Finance and Economics,2019.

Hu Hanqing, Shen Peng, Zhang Zesheng, Wan Ni. A comparative study of inbound tourists number forecasting in Beijing based on ARIMA and NARX[J]. Journal of Beijing University of Information Science and Technology (Natural Science Edition),2020,35(05):9-13.

Lin Zeming, Huang Yue-Ling, Lin Ming-Ming, Zhuang Cheng-Ping. Analysis of the interaction between agriculture and tourists in Guilin City and countermeasures for integrated development--based on VAR model and Granger causality test[J]. Journal of Guilin University of Technology:1-9.

Su Xin. Research on apparel sales forecasting based on Prophet-LSTM combined model[D]. Jiangsu University of Science and Technology,2020.

Peng Pei,Liu Min. Short-term load forecasting method based on Prophet-LSTM combinatorial model[J]. Journal of Power Systems and Automation,2021,33(11):15-20.

Xu pei, Fan Chongjun, Zhu Renjie, Huang Nai. Research on hospital inpatient volume prediction based on Prophet-LSTM-PSO combined model[J]. Journal of Shanghai University of Technology, 2021, 43(01): 68-72.

Zu Peifu, Chu Wenjie. Research on predicting the number of tourists in Mudanjiang based on grey linear regression combined prediction model[J]. Practice and understanding of mathematics,2020,50(13):280-286.

Gong Yanyuan, Ai Hongzhi. Research on overseas tourists number prediction model with RBF neural network[J]. Computing Technology and Automation,2020,39(04):159-162.

Li Junyin, Li Yue. Forecasting and analysis of the number of inbound tourists in China--based on ARIMA multiplier seasonal model[J]. Inner Mongolia Statistics,2019(05):26-30.

Chen Meilin, He Qinglong. Research on tourists number prediction in Guizhou province based on entropy power method hybrid model[J]. Practice and understanding of mathematics,2018,48(21):307-313.

Wang Xiao, Tui Jinhua, Zhang Liheng. Research on railroad passenger flow prediction based on Prophet algorithm[J]. Computer Technology and Development,2020,30(06):130-134+150.

Wang Wei. Application of optimal combined forecasting linear model in tourists demand forecasting--a case study of mainland China's tourist volume forecasting to Macau[J]. Practice and understanding of mathematics,2018,48(12):49-58.

Li Yuxin, Dai Min, Wang Peng. An empirical test of the interaction between domestic and foreign trade development and industrial structure in China[J]. Statistics and Decision Making,2022,38(02):109-113.

Li Jie, Lin Yongfeng. Time-series data prediction based on multi-timescale RNN[J]. Computer Application and Software,2018,35(07):33-37+62.

He Xiangzhou, Yang Jiahua. Blockchain economic mechanism and rural revitalization strategy [J]. Journal of Anhui Administrative College,2020(2):68-75.

Liu Yuxi, Jiang Zeshi, Gu Beier, Xu Nanfeng. Exploring the path of blockchain technology to promote rural tourists development[J]. Shanxi Agricultural Economics,2021(22):53-55.

Li Yuan, Chen Qin, Zhang Shulin. A review of domestic rural tourists development model[J]. Journal of Zhejiang Wanli College,2013,26(6):34-38.