A EMD-BP integrated model to forecast tourist number and applied to Jiuzhaigou

Issue title: Artificial Intelligent Techniques and its Applications

Guest editors: Mahalingam Sundhararajan, Xiao-Zhi Gao and Hamed Vahdat Nejad

Article type: Research Article

Authors: Shao-Jiang, Lin^a | Jia-Ying, Chen^{b; *} | Zhi-Xue, Liao^c

Affiliations: [a] College of Tourism, Sichuan Agricultural University, Dujiangyan, China | [b] Business School, Sichuan Agricultural University, Dujiangyan, China | [c] School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China

Correspondence: [*] Corresponding author. Chen Jia-Ying, Business School, Sichuan Agricultural University, Dujiangyan 611830, China. E-mail: uggzqp@163.com.

Abstract: This paper focuses on improving the accurate prediction of tourist capacity, which is the key to solve the contradiction of tourism economy development and ecological environment protection. EMD-BP integrated predictive model is proposed and uses Empirical Model Decompose method to decompose time-series data of visitors into several TMF, then forecasting each component by BP neural network. In order to shown the effective of our method, an empirical study of Jiuzhaigou is conducted, and the average error rate of EMD-BP integrated prediction model is 8.8%, among which the error within 1% accounts for 31.3% of the total predicted amount, the error within 5% accounts for 41.7%, the error above 10% accounts for 30.2% in slack seasons and 69.8% in busy seasons.

Keywords: Empirical Model Decompose, BP neural network, integrated prediction method, JiuZhaigou

DOI: 10.3233/JIFS-169398

Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 2, pp. 1045-1052, 2018