• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.412-414
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• 2017

It is important to predict price of agricultural products accurately to government, local government, bodies in charge of agriculture. Production and shipping of agricultural products are affected by weather condition significantly. In this research, prediction model of a Chinese cabbage which is highly sensitive to weather condition is proposed using deep learning technique. After performance of proposed model and a model of previous research is compared, superiority of proposed model is proved.

• Smart Media Journal
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• v.13 no.1
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• pp.9-17
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• 2024

This study aims to develop an integrated agricultural distribution network management system to improve the quality, profit, and decision-making efficiency of agricultural products. We adopt two key techniques: crop maturity detection based on the YOLOX target detection algorithm and market price prediction based on the Prophet model. By training the target detection model, it was possible to accurately identify crops of various maturity stages, thereby optimizing the shipment timing. At the same time, by collecting historical market price data and predicting prices using the Prophet model, we provided reliable price trend information to shipping decision makers. According to the results of the study, it was found that the performance of the model considering the holiday factor was significantly superior to that of the model that did not, proving that the effect of the holiday on the price was strong. The system provides strong tools and decision support to farmers and agricultural distribution managers, helping them make smart decisions during various seasons and holidays. In addition, it is possible to optimize the distribution network of agricultural products and improve the quality and profit of agricultural products.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.778-783
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• 2006

Price prediction is essential to decisions of investment and shipment in oak mushroom cultivation. But predicting the prices of oak mushroom is very difficult because there are so many uncertain factors affecting the demand and the supply in the market. The Box-Jenkins methodology is one of strong tools in price prediction especially for the short-term using historical observations of time series. In this paper, the Box-Jenkins methodology is applied to find a model to forecast future oak mushroom prices. And out-of-sample test was conducted to check out the prediction accuracy. The result shows the high accuracy except for market disturbance period affected by unexpected weather change and reveals the usefulness of the model.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2002.07a
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• pp.400-406
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• 2002

현대농업의 한 부분인 축산업은 우리나라 경제에 큰 비중을 차지하고 있다. 축산업의 자동화 및 무인화는 현재 농촌의 인력부족 문제를 해결할 뿐만 아니라, 우리 농민의 수익도 높일 수 있으며, 나아가서 우리 농업의 국제경쟁력을 제고할 수 있다. 영국 등 다른 선진국에서는 자국의 양돈농가를 위하여 돼지의 무게를 예측할 수 있는 돼지의 무게를 예측시스템을 개발하였다. 돼지 무게 예측시스템은 돼지의 무게를 예측할 수 있으므로 가격이 좋은 시기에 사육한 돼지를 출하함으로써 농가의 소득에 많은 기여를 하고 있다. 지금 우리 축산업 농가의 양돈업 기계화는 이미 실현되었으나 관리 자동화면에서 아직 많이 부족하다. 그 중에 하나가 바로 돼지의 무게 측정이다. (중략)

• Journal of Agricultural Extension & Community Development
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• v.22 no.4
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• pp.423-434
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• 2015

This paper predicts the onion's cultivation areas, yields per unit area, and wholesale prices during ship dates by using wholesale price data from the Korea Agro-Fisheries & Food Trade Corporation, the production data from the Statistics Korea, and the weather data from the Korea Meteorological Administration with an ARDL model. By analyzing the data of wholesale price, rural household income and rural total earnings, onion cultivation areas in 2015 are estimated to be 21,035, 17,774 and 20,557(ha). In addition, onion yields per unit area of South Jeolla Province, North Gyeongsang Province, South Gyeongsang Province, Jeju Island, and the whole country in 2015 are estimated to be 5,980, 6,493, 6,543, 6,614, 6,139 (kg/10a) respectively. By using onion production's predictive value found from onion's cultivation areas and yields per unit area in 2015, the onion's wholesale prices in June are estimated to be 780 won, 1,100 won, and 820 won for each model. Predicted monthly price after the onion's ship dates is analyzed to exceed 1,000 won after August.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.617-624
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• 2017

The production of cabbage, which is mainly cultivated in open field, varies greatly depending on weather conditions, and the price fluctuation is largely due to the presence of a substitute crop. Previous studies predicted the production of cabbage using actual weather data, but in this study, we predicted the wholesale price using unstructured agricultural meteorological data on the web. From January 2009 to October 2016, we collected documents including the cabbage on the portal site, and extracted keywords related to weather in the collected documents. We compared the forecast wholesale prices of simple models and unstructured agricultural weather models at the time of shipment. The simple model is AR model using only wholesale price, and the unstructured agricultural weather model is AR model using unstructured agricultural weather data additionally. As a result, the performance of unstructured agricultural weather model was has been found to be more accurate prediction ability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.305-309
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• 2002

In this paper, we present a standard S/W solution for nursery administration. This S/W would substitute for classical nonscientific nursery management that has depended on personal experience and intuition. Especially, the suggest S/W based on its early model(Hwangkum-a-jang) is designed to operate on its daily diary writing. It means every statistical data and information for a sales can be calculated by self analyzing function just by keeping a diary.

• Journal of the korean Society of Automotive Engineers
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• v.2 no.2
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• pp.16-20
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• 1980

1970년대초의 오일, 쇼크에 이어 현재는 제2차 석유파동에 들어서고 있다. 이의 발단이 된 .78 년말의 이란정변은 이란석유의 감산에 따라 세계적인 공급이 부족하게 되었다. 이에 따라 .79년 초부터 원유가격이 뜀박질하는 결과를 가져와 세계의 Energy가치는 급속한 템포로 변화하였다. 더욱이 1980년 9월부터 2개월 이상을 끌어온 이란-이라크전쟁은 대폭적인 석유감산과 중동산의 원유유통의 문제화 등으로 바렐(bl:Barrel)당 2$의 공식적인 인상과 현물시장가격의 20% 유가 인상은 석유소비국들을 공포의 도가니로 몰아 넣고 있다. 특히 OPEC(석유수출국기구)의 정책은 자원의 보호라는 미명아래 이른바 "More money for less oil"(생산은 적게 수입은 보다 많이) 라는 말로 생산을 억제하면서 원유가격을 인상하여 수입을 증가시키는 방향으로 변해가고 있다. 이와 같은 석유가격의 고등과 공급이 불안정한 상황하에서 미래의 석유사정을 예측한다는 것은 어려운 일이나, 지금까지 발표된 문헌들을 기초로 미루어 보아 금후의 석유사정과 이것이 자 동차용 연료에 어떠한 영향을 미치나 살펴보기로 한다. 살펴보기로 한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.329-335
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• 2023

Avocado, a superfood selected by Time magazine and one of the late ripening fruits, is one of the foods with a big difference between local prices and domestic distribution prices. If this sorting process of avocados is automated, it will be possible to lower prices by reducing labor costs in various fields. In this paper, we aim to create an optimal classification model by creating an avocado dataset through crawling and using a number of deep learning-based transfer learning models. Experiments were conducted by directly substituting a deep learning-based transfer learning model from a dataset separated from the produced dataset and fine-tuning the hyperparameters of the model. When an avocado image is input, the model classifies the ripeness of the avocado with an accuracy of over 99%, and proposes a dataset and algorithm that can reduce manpower and increase accuracy in avocado production and distribution households.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.141-153
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• 1986

This study intends to document the existing cyclical fluctuations of garic and onion price at farm gate level during the period of 1966-1986 in Korea. The existing patterns of such cyclical fluctuations were estimated systematically by removing the seasonal fluctuation and irregular movement as well as secular trend from the original price through the moving average method. It was found that the cyclical fluctuations of garic and onion prices repeated six and seven times respectively during the same period, also the amplitude coefficient of cyclical fluctuations showed speed up in recent years. It was noticed that the cyclical fluctuations of price in onion was higher than that of in garic.