• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.1-10
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• 2022

Vegetables such as cabbage are greatly affected by natural disasters, so price fluctuations increase due to disasters such as heavy rain and disease, which affects the farm economy. Various efforts have been made to predict the price of agricultural products to solve this problem, but it is difficult to predict extreme price prediction fluctuations. In this study, cabbage prices were analyzed using the ensemble Voting technique, a method of determining the final prediction results through various classifiers by combining a single classifier. In addition, the results were compared with LSTM, a time series analysis method, and XGBoost and RandomForest, a boosting technique. Daily data was used for price data, and weather information and price index that affect cabbage prices were used. As a result of the study, the RMSE value showing the difference between the actual value and the predicted value is about 236. It is expected that this study can be used to select other time series analysis research models such as predicting agricultural product prices

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.619-622
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• 2015

Recently, there are growing fluctuations of productivity and price caused by severe weather conditions in the agriculture. Yield forecasting methods have been studied to solve the problems. This paper predicted yield per area, production area, and elements of weather based on the linear equation. A yield is calculated by multiplying the production area times the yield per area that is compensated using the weighted sum of the elements of weather. In experiments, proposed method shows that a forecasting precision is the more than 90%.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.29-36
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• 2022

In this paper, we propose an efficient agricultural products price prediction model based on dataset which provided in DACON. This model is XGBoost and CatBoost, and as an algorithm of the Gradient Boosting series, the average accuracy and execution time are superior to the existing Logistic Regression and Random Forest. Based on these advantages, we design a machine learning model that predicts prices 1 week, 2 weeks, and 4 weeks from the previous prices of agricultural products. The XGBoost model can derive the best performance by adjusting hyperparameters using the XGBoost Regressor library, which is a regression model. The implemented model is verified using the API provided by DACON, and performance evaluation is performed for each model. Because XGBoost conducts its own overfitting regulation, it derives excellent performance despite a small dataset, but it was found that the performance was lower than LGBM in terms of temporal performance such as learning time and prediction time.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.706-708
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• 2017

노지에서 재배되는 실외작물의 경우 외부 환경에 노출되어 재배되기에 생육 또는 수학시기가 외부 요인에 많은 영향을 받는다. 이러한 외부 요인 중 과일의 당도 및 수확량에 많은 영향을 미치는 요인은 바로 날씨이다. 고온의 날씨 또는 저온의 날씨가 지속되거나 강한 풍속, 적절한 강수가 이루어지지 않을 경우 과일의 당도가 낮아지거나, 흠집이 발생할 수 있어 과일 도매가격에 영향을 미치게 된다. 본 논문에서는 월별 평균 온도, 강우량, 습도, 일사량, 최대풍속 등의 날씨 관련 데이터와 제사 또는 명절에 자주 사용되는 과실류인 배, 단감, 사과, 수박의 도매가격간의 상관관계를 분석을 통해 얻은 결과로 추후 농산물 가격 예측 또는 과일 가격 예측 연구에 기여를 하고자 한다.

• Journal of the Korean Geographical Society
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• v.31 no.4
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• pp.648-661
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• 1996

The traditional von Thunen model has various shortcomings. Perhaps the greatest dificiency is the model's sole emphasis on the production side of the economy;that is, the agricultural markets are rarely closed for demand. In thes paoer a closed model for a three-activity, two-dimensional economy is developed. Equillibrium solutions are generated for prices, land areas, and outputs. Comparative static analysis then follows. Attention is next given to a maximum expected-return model under environmental uncertainty. Land uses for the traditional model and the closed model are then compared.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.137-153
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• 2016

The price of agricultural products has changed from year to year, the m ajor c ause o f price fluctuation is the imbalance of supply and demand. Materials which are mainly used in korean cabbage production volume is the forecast model, using the cadastral result, slope calculation is impossible to achieved. For this reason, this implies the drastic decrease of prices and the prediction of supply and demand of field crops that is cultivated in a highland slope area, this situation is being repeated. Therefore, the target area of this research is the slopes of high land, by using 2D and 3D Lidar data for the analysis of the cultivated area. Experiment was carried out in the same area to compare the data differences. The rate of change in the area of slope is quantitatively increasing presented by the regression model. An alternative methodology that can improve the reliability of the calculated slope area using 2D is through cadastral map.

• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.359-367
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• 2015

Geographical Indication (GI) has been used with the expectation to influence customer buying behavior. In this research, we empirically investigate if such relationship exists using apple price changes in Korea along with web search traffic reflecting customers' interest in GI. The experimental results indicate that the apple price of the past, apple supply and web search traffic including GI name were significant on the prediction of price change of Chungju while web search traffic of regional name and that of product were significant for Cheongsong apples with GI. In Yeongcheon with no GI, the apple price of the past turns out to be significant only. The results indicated that interests in GI can help the price prediction but the regional name itself can play the same role, if the GI product is well known in association with the region.

• KOREAN POULTRY JOURNAL
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• v.8 no.8 s.82
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• pp.119-122
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• 1976

지난 10년간의 돌이켜보면 국내양계업계는 장족의 발전을 거듭하였다. 그러나 이와 비례하여 양계업자간의 경쟁이 그만큼 치열해졌다. 뿐만 아니라 장래에는 외국의 양계업계와 어깨를 나란히 하여 그들과 경쟁할 경우도 예상하여야 할 것이다. 이와 같이 업계의 격화하여가는 경쟁에서 낙오되지 않고 업체를 유지하며 경쟁에서 승리하자면 무엇보다도 양계기술의 향상과 경영의 합리화 및 생산성 향상을 꾀하고 생산비용의 절감에 주력하지 않을 수 없게 되었고 75년도 말로서 감면기간은 끝나 금년도부터는 소득금액의 50$\%$에 상당하는 세금이 부과될지도 모른다는 사실을 두고 볼 때 과거 어느 때보다도 양계 경영 기장에 유의하지 않을 수 없다 하겠다. 특히 양계경영은 내일을 예측할 수 없는 경영난의 어려움을 항상 가져야 한다는 것과 농산물도 마찬가지 이겠으나 양계업의 주산물인 계란과 육계의 가격을 시장에서 형성된다는 점에서 보다 합리적인 기장의 필요성을 갖게 되는 것이다. 다른 공산품의 제조와 달리 양계업의 제조(생산)과정의 기장에는 이렇다할 기장원칙이 성립되지 않는 본 업계의 문제점을 두고 볼 때에 비용의 처리에 세심한 주의를 요한다. 이에 본인은 업계의 추세를 중시하고 국내외의 서적과 이 분야에서의 경험과 타업종에서 추진되고 있는 기장의 합리화와 원가계산제도의 경향을 바탕으로 하여 양계경영에 적용될 생산원가산출과 기장에 대하여 부족하나마 $\ulcorner$월간양계$\lrcorner$에 게재하면서 함께 연구하고자 한다.