Agricultural product future price prediction method and system based on text mining and deep learning model

• Main Authors: LIN RUIBIN, ZENG ZHIMEI, LYU XING, YU ZEHUI, HUANG JUNJIE, ZHANG XUEJING, ZHANG DABIN
• Format: Patent
• Language: Chinese; English
• Published: 06.01.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses an agricultural product future price prediction method and system based on text mining and a deep learning model. The method comprises the steps of collecting agricultural product future historical transaction data and agricultural product future news text data and performing data preprocessing; selecting T days as window sliding to divide a data set, and taking the obtained data set as a multi-feature data sample; extracting price features by using a bidirectional long short-term memory neural network (BiLSTM); extracting text features by using a convolutional neural network (textCNN); extracting news emotion features by using the snowNLP; and constructing a deep neural network, fusing the three features, and predicting the agricultural product future closing price one step ahead. According to the method, market and non-market factors influencing agricultural product future price fluctuation are considered, the agricultural product future price trend is predicted based on the text min