Price forecast of Yunnan Pu’er tea based on the MLP neural network

Article type: Research Article

Authors: Dou, Zhiwu | Ji, Mingxin^* | Yuan, Zhihui | Li, Haibo

Affiliations: Yunnan University of Finance and Economics, Kunming, Yunnan, China

Correspondence: [*] Corresponding author: Mingxin Ji, Yunnan University of Finance and Economics, Kunming, Yunnan, China. E-mail: [email protected].

Abstract: Pu’er tea as the landmark product of Yunnan province, which plays a decisive role in the national tea industry and the economic development of Yunnan province. At present, the qualitative and quantitative methods cannot be accurately predicted the price of Pu’er tea. In order to solve this problem, this paper tries to use MLP neural network to forecast Pu’er tea price. Firstly, determine the influencing factors of Pu’er tea price, then established the MLP neural network model, selection activation function and design the number of neurons and the hidden layer size, finally compare the method between MLP and random forest to verify the feasibility and effectiveness of the MLP method.

Keywords: MLP neural network, random forest, price predict

DOI: 10.3233/JCM-194060

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 20, no. 3, pp. 807-815, 2020