Title:	PREDICTION OF AGRICULTURAL PRODUCTS PRICE WITH LSTM NETWORK
Author(s):	Sungho Shin, Mikyung Lee, Seongchan Kim and Sa-Kwang Song
ISBN:	978-989-8533-72-2
Editors:	Piet Kommers, Tomayess Issa, Pedro Isaías and Ana Hol
Year:	2017
Edition:	Single
Keywords:	Agricultural Product, Deep Learning, LSTM, Natural Disasters, Price Prediction
Type:	Short Paper
First Page:	169
Last Page:	174
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	There is considerable interest and research on issues that threaten the safety of mankind, such as natural disasters and disease propagation. This is because although the frequency of these events is low, even a single such incident may cause numerous human casualties and asset damages. Typhoons and floods are natural disasters that occur frequently, and the damage resulting from these disasters must be estimated to establish appropriate countermeasures. Although there are many primary damages that result from natural disasters such as demolished buildings, human casualties, and loss of farms and fields, there are also secondary damages such as increased consumer prices. The price of agricultural products is one of the main consumer prices that are influenced by typhoons and floods. Sudden, powerful typhoons are accompanied by heavy rains that damage agricultural products; this makes consumers apprehensive about availability and subsequently increases the retail price of such products. This study analyzes the effect of natural disasters on the price of agricultural products by using the deep learning algorithms. To elaborate, this study used data on variables that influence the price of agricultural products to create a model that can predict changes in the price of agricultural products. The study results showed that the model’s accuracy was at 0.15 based on RMSE standards, which means that it could suitably explain the changes in agricultural product prices. Accurate predictions about the price of agricultural products using the study results can be utilized by the government to formulate policies to prepare for natural disasters, such as the required scale of supply of agricultural products and amount of imports.
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