신뢰성 해석기법을 이용한 배추 가격폭등 예측 모형의 개발
Reliability Analysis for Price Forecasting of Chinese Cabbage
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초록
Generally the price of agricultural products has much different characteristics from that of manufacturing products. If products have the limitation of long-term storage and the short period of cultivation, the price of products can be more unstable. Moreover, the price forecasting is very difficult because it doesn't follow any cycle or trend. However price can be regarded as risk instead of uncertainty if we can calculate the probability of price. Reliability analysis techniques are used for forecasting the price change of chinese cabbage. This study aims to show the usability of reliability analysis for price forecasting. A price-forecasting model was developed based on weather data of 10 days before 70 days and the average price and standard deviation of wholesale market prices from 1996 to 2001 and applied to forecast the boom price of upland Chinese cabbage in 2002 and 2003. Applied results showed the possibility of boom price forecasting using reliability analysis techniques.
Abstract
Generally the price of agricultural products has much different characteristics from that of manufacturing products. If products have the limitation of long-term storage and the short period of cultivation, the price of products can be more unstable. Moreover, the price forecasting is very difficult because it doesn't follow any cycle or trend. However price can be regarded as risk instead of uncertainty if we can calculate the probability of price. Reliability analysis techniques are used for forecasting the price change of chinese cabbage. This study aims to show the usability of reliability analysis for price forecasting. A price-forecasting model was developed based on weather data of 10 days before 70 days and the average price and standard deviation of wholesale market prices from 1996 to 2001 and applied to forecast the boom price of upland Chinese cabbage in 2002 and 2003. Applied results showed the possibility of boom price forecasting using reliability analysis techniques.
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