• 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.

• 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 KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.331-344
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• 2009

Recently, it is expected that the agricultural and stockbreeding industry are damaged by the China-Japan-South Korea FTA and FTA between the United States and South Korea. After free trade, it is increasing to import crops, aquatic products, and livestock which are produced in a foreign land. But it is affected negatively to the trust relationships and markets, because of breaking it out that low grade foreign products are turned into domestic products. For this reason, we need the traceability management system. In this paper, it designs and implements the traceability management system using RFID and USN providing distribution traceability information as well as the traceability information of the growth environment, automatic control according to the facility growing and monitoring of the storehouse. The implemented whole systems consist of the growth environment monitoring and the traceability management. First, the growth environment monitoring shows the environment of plantation and automatic controller of the storehouse and growing facility. This growth environment monitoring information provides the detailed information about growth environment and writing the farming diary automatically by producer. Second, the traceability management provides all of the traceability information such as production, shipment and consumption to consumers. The traceability management system that has been designed and implemented using RFID and USN in this paper, provides the u-IT agriculture to producer and the reliability about agricultural products. In addition, this system provides the foundation data to operate GAP and HACCP, and becomes the advantaged agricultural products of the interior of a country by application of this system.

• International Commerce and Information Review
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• v.13 no.1
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• pp.29-52
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• 2011

A predictable and manageable output is desirable for most businesses. However, it is very difficult to control the quality and quantity of products in the food and agriculture business. Predictable outputs help managers plan their marketing, sales, and inbound and outbound logistics, but these are not easy to achieve in the food and agriculture business. Various industries have adopted different levels of automation and utilization of information systems for quality/quantity control; however e-Commerce of the food and agriculture industry is far behind those of other industries. Today, the food and agriculture industry is supposed to be more integrated than ever in order to reduce risks and improve processing costs, from farm to table. Since its operations including production, processing, storage, distribution, and management are dispersed all over the world, the food and agricultural industries now depend more on IT than other industries. This study attempts to develop a framework to analyze the current situation of agricultural product e-Commerce in Korea, and finds out the actual situation of the farmers operating on-line shopping systems through the developed framework and suggests some improvements.

• Journal of Practical Agriculture & Fisheries Research
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• v.16 no.1
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• pp.193-206
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• 2014

The objectives of the project are to increase farmers' income through GAP and to reduce the loss of agricultural produce, for which the Korean partner takes a role of transferring needed technologies to the project site. To accomplish the project plan, it is set to implement the project with six components: construction of buildings, installation of agricultural facilities, establishment of demonstration farms, dispatching experts, conducting training program in Korea and provision of equipments. The Project Management Committee and the Project Implementation Team are consisted of Korean experts and senior officials from Department of Agriculture, Myanmar that managed the project systematically to ensure the success of the project. The process of the project are; the ceremony of laying the foundation and commencing the construction of training center in April, 2012. The Ribbon Cutting Ceremony for the completion of GAP Training Center was successfully held under PMC (MOAI, GAPI/ARDC) arrangement in SAl, Naypyitaw on June 17, 2012. The Chairman of GAPI, Dr. Sang Mu Lee, Director General U Kyaw Win of DOA, officials and staff members from Korea and Myanmar, teachers and students from SAl attended the ceremony. The team carried out an inspection and fixing donors' plates on donated project machineries, agro-equipments, vehicles, computers and printer, furniture, tools and so forth. Demonstration farm for paddy rice, fruits and vegetables was laid out in April, 2012. Twenty nine Korean rice varieties and many Korean vegetable varieties were introduced into GAP Project farm to check the suitability of the varieties under Myanmar growing conditions. Paddy was cultivated three times in DAR and twice in SAl. In June 2012, vinyl houses were started to be constructed for raising seedlings and finished in December 2012. Fruit orchard for mango, longan and dragon fruit was established in June, 2012. Vegetables were grown until successful harvest and the harvested produce was used for panel testing and distribution in January 2013. Machineries for postharvest handling systems were imported in November 2012. Setting the washing line for vegetables were finished and the system as run for testing in June 2013. New water tanks, pine lines, pump house and electricity were set up in October 2013.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.1
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• pp.114-119
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• 2013

The superiority and safety of eco-friendly agricultural products are well-known. The purpose of this study is to provide fundamental data for creating a safe food culture, to improve the quality of school food services, and to increase student satisfaction with school food services. We compared the perception of eco-friendly agricultural products and food service satisfaction between students with and without exposure to a dedicated event for learning about eco-friendly products (an Eco-friendly Food Service Day) in elementary and middle school. When students were asked to define eco-friendly products, "organic products" was a highly frequent response in schools with an Eco-friendly Food Service Day, while "pesticide-free products" was a highly frequent response in school without this event. For most students, a factor in choosing eco-friendly products was a quality certification mark. Students from elementary schools with an Eco-friendly Food Service Day had a higher frequency of using eco-friendly agricultural products at home compared to students from schools without the event (p<0.01). In addition, the satisfaction with school food service was higher in schools with an Eco-friendly Food Service Day (p<0.05). These results suggest it is important to promote the use of superior and safe eco-friendly agricultural products while developing a variety of menus considering students' preferences.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.201-207
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• 2023

In this paper, we propose an optimal model for mid to long-term price prediction of agricultural products using LGBM, MLP, LSTM, and GRU to compare and analyze the three strategies of the Multi-Step Time Series. The proposed model is designed to find the optimal combination between the models by selecting methods from various angles. Prior agricultural product price prediction studies have mainly adopted traditional econometric models such as ARIMA and LSTM-type models. In contrast, agricultural product price prediction studies related to Multi-Step Time Series were minimal. In this study, the experiment was conducted by dividing it into two periods according to the degree of volatility of agricultural product prices. As a result of the mid-to-long-term price prediction of three strategies, namely direct, hybrid, and multiple outputs, the hybrid approach showed relatively superior performance. This study academically and practically contributes to mid-to-long term daily price prediction by proposing an effective alternative.

• 월간낙농육우
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• v.29 no.12
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• pp.150-155
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• 2009

송장목장은 그야말로 땅과 함께 더불어 사는 '시골 목장'이다. 착유소가 33마리. 결코 대농이라 부를 수 없는 규모로 우유 뿐 아니라 쌀부터 버섯, 고추, 마늘 등 어지간한 농산물을 목장 주변 곳곳에서 직접 농사지어 먹고 있다. 그래서 목장을 찾은 이들에게 이것저것 내줄 것이 많은, 인심 좋은 '시골집' 이다.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2006.11a
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• pp.547-549
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• 2006

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2006.11a
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• pp.550-553
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• 2006