Short-term forecasting of vegetable prices based on LSTM model—Evidence from Beijing’s vegetable data

The vegetable sector is a vital pillar of society and an indispensable part of the national economic structure. As a significant segment of the agricultural market, accurately forecasting vegetable prices holds significant importance. Vegetable market pricing is subject to a myriad of complex influe...

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Bibliographic Details
Published in:	PloS one Vol. 19; no. 7; p. e0304881
Main Authors:	Zhang, Qi, Yang, Weijia, Zhao, Anping, Wang, Xiaodong, Wang, Zengfei, Zhang, Lin
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 11.07.2024 Public Library of Science (PLoS)
Subjects:	Accuracy Agricultural production Beijing Biology and Life Sciences Commerce - economics Commerce - trends Computer and Information Sciences Datasets Decision making Deep learning Economic forecasting Forecast accuracy Forecasting Forecasts and trends Humans Industrial development Learning algorithms Machine Learning Market prices Models, Economic Neural networks Performance prediction Physical Sciences Prices and rates Pricing Research and Analysis Methods Stability augmentation Statistical analysis Stochastic models Supply & demand Supply chains Support vector machines Sustainable development Time series Vegetable industry Vegetables Vegetables - economics Vegetables - growth & development Wavelet transforms Beijing China Beijing China
ISSN:	1932-6203, 1932-6203
Online Access:	Get full text
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