{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:41:46Z","timestamp":1776811306632,"version":"3.51.2"},"reference-count":18,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2020,9,30]]},"abstract":"<jats:p>Pu\u2019er 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\u2019er tea. In order to solve this problem, this paper tries to use MLP neural network to forecast Pu\u2019er tea price. Firstly, determine the influencing factors of Pu\u2019er 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.<\/jats:p>","DOI":"10.3233\/jcm-194060","type":"journal-article","created":{"date-parts":[[2020,2,11]],"date-time":"2020-02-11T10:50:45Z","timestamp":1581418245000},"page":"807-815","source":"Crossref","is-referenced-by-count":0,"title":["Price forecast of Yunnan Pu\u2019er tea based on the MLP neural network"],"prefix":"10.66113","volume":"20","author":[{"given":"Zhiwu","family":"Dou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingxin","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihui","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haibo","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"1","key":"10.3233\/JCM-194060_ref1","first-page":"24","article-title":"Investigation on farmers of Pu\u2019er tea in Yunnan Tea","volume":"39","author":"Xu","year":"2012","journal-title":"Journal of Tea"},{"key":"10.3233\/JCM-194060_ref2","unstructured":"L. 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Jiang, Prediction of landslide displacement time series based on regression neural network, Huazhong University of Science and Technology, 2017."},{"issue":"20","key":"10.3233\/JCM-194060_ref19","first-page":"191","article-title":"Exploration and practice of flower price prediction platform design","author":"Qian","year":"2018","journal-title":"Northern Horticulture"},{"key":"10.3233\/JCM-194060_ref20","unstructured":"C. Liu and J. 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