STL-ATTLSTM: Vegetable Price Forecasting Using STL and Attention Mechanism-Based LSTM - Yin, Helin; Jin, Dong; Gu, Yeong Hyeon; Park, Chang Jin; Han, Sang Keun; Yoo, Seong Joon (Agriculture (Basel), 2020)
Keywords: Accuracy; Agricultural production; Agriculture; attention mechanism; Back propagation; cabbage; Climate change; Consumers; Crop production; Decomposition; Deep learning; Forecasting; Garlic; Genetic algorithms; hot peppers; loess; Long short-term memory; LSTM; Machine learning; markets; Mathematical models; Meteorological data; Model accuracy; Neural networks; onions; prediction; Predictions; Prices; Pricing; radishes; Regression analysis; Root-mean-square errors; Seasonal variations; Statistical methods; STL; Supply & demand; Support vector machines; Time series; time series analysis; Trends; vegetable price forecasting; Vegetables; Weather; China