ARIMA和LSTM预测斯里兰卡科伦坡蔬菜零售价格的比较

Dinuk D. Fonseka, A. Karunasena
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引用次数: 1

摘要

确定蔬菜价格趋势对于在生产和市场中做出更好的决策非常重要。由于季节性、易腐性、供需市场不平衡、客户选择和原材料供应等因素,蔬菜价格波动迅速,极不稳定。利用2009 - 2018年科伦坡白菜、胡萝卜和四季豆零售价格数据,采用ARIMA和LSTM模型进行价格预测。根据RMSE和MAPE的决策准则,LSTM模型在预测蔬菜零售价格方面优于ARIMA模型。在斯里兰卡蔬菜市场上,还没有研究集中于用新技术预测价格。因此,本研究的结果可用于斯里兰卡政府和农业决策者建立先进的预测模型。
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Comparison of ARIMA and LSTM in Forecasting the Retail Prices of Vegetables in Colombo, Sri Lanka
Identification of vegetable price trends is important to make better decisions in the production and market. Due to several factors, including seasonality, perishability, an imbalanced supply-demand market, customer choice, and the availability of raw materials, vegetable prices fluctuate quickly and are highly unstable. In this study price prediction was concluded using two models ARIMA and LSTM with retail price data for Cabbage, Carrot, and Green beans in Colombo from 2009 to 2018. According to the decision criteria of RMSE and MAPE, the LSTM model is superior to the ARIMA model in predicting the retail prices of vegetables. There were no studies have focused on predicting prices with novel technology in the Sri Lankan vegetable market. Hence the results of this study can be used to build an advanced forecasting model by the government and decision-makers in agriculture in Sri Lanka.
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