• The Korea Beekeeping Bulletin
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• s.344
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• pp.22-25
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• 2009

지난해, 극심한 아카시아 벌꿀 흉년으로 벗어나 평년작을 달성해 양봉농가의 시름을 덜었다 했다. 그러나 올해는 더욱 예측불가능해진 기상이변으로 2004년 수준의 대흉작이 예고 되고 있다. 남부지역은 극심한 봄 가뭄으로 아까시나무가 개화 하자마자 빠르게 시들어 버렸으며 가뭄현상이 비교적 약했던 경상 북부지역은 개화 후 큰 폭의 일교차로 꿀 생산량 감소했다. 중부 경기북부지역은 5월 아까시 꽃의 개화 후 잦은 비로 인해 아카시아 벌꿀생산량이 바닥을 보였다. 강원 일부 지역에서는 채밀을 전혀 못한 곳도 있어 심각한 수준이다. 여기에 잠잠해졌던 아까시 나무 황화현상까지 다시 번지고 있는 실정이다.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.47-55
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• 2000

In oreder to predict the productions of major crops such as rice, barely, soybean and potato in Kyongsang Puk Do as early as possible, an attempt has been made to develop some prediction model of crop yields, using the data from the Statistical Yearbooks of Agriculture, Forestry and Fisheries from 1966 through 1999. Among the various models considered, $y=\exp({\beta}_{0}+{\beta}_{1}t+{\epsilon})$ was best fit to the planted area of the crops and $y=\exp({\beta}_{0}+{\beta}_{1}t^{1/2}+{\beta}_{2}t+{\sum}^{p}_{i=1}{\beta}_{i}+_2x_i+{\epsilon})$ to the yields. The $R^{2}$ values for the planted areas were $0.9180{\sim}0.9505$, implying good prediction, while that for rice was 0.7234 and those for barley, soybean and potato were $0.8855{\sim}0.9098$, Predictions have also been made for the planted areas upto the year 2005 and yield for the year 2000.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.29-37
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• 2023

Due to climate change, interest in crop production and distribution is increasing, and attempts are being made to use bigdata and AI to predict production volume and control shipments and distribution stages. Prediction of agricultural product imports not only affects prices, but also controls shipments of farms and distributions of distribution companies, so it is important information for establishing marketing strategies. In this paper, we create an artificial intelligence prediction model that predicts the future import volume based on the wholesale market melon import volume data disclosed by the agricultural statistics information system and evaluate its accuracy. We create prediction models using three models: the Neural Prophet technique, the Ensembled Neural Prophet model, and the GRU model. As a result of evaluating the performance of the model by comparing two major indicators, MAE and RMSE, the Ensembled Neural Prophet model predicted the most accurately, and the GRU model also showed similar performance to the ensemble model. The model developed in this study is published on the web and used in the field for 1 year and 6 months, and is used to predict melon production in the near future and to establish marketing and distribution strategies.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.4
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• pp.291-298
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• 2024

As an important fishing ground in the southern coast of Korea, Jinhae Bay is characterized by a high level of fisheries production. However, its marine-ecosystem has shifted owing to environmental changes such as industrial development and high water temperatures over the decades. This study analyzes the fisheries production, discards, mean trophic level, and fishing-in-balance index using annual fishing data from five regions surrounding Jinhae Bay for the period 2005-2022, as well as using additional forecasting trends by 2027 using ARIMA (Auto Regressive Intergrated Moving Average). The results shows, that the production in Goseong will decrease continuously by 2027, as compared with that in other areas. Additionally, byproduct management is considered necessary in Tongyeong. For the marine-ecosystem index, Tongyeong indicates stable catch ratio of large fish species and a fishing-in-balance exceeding 0. Finally, the annual catch variation for six pelagic fish species in Jinhae Bay by 2060 is estimated based on the IPCC climate-change scenario, in which the recent low level that decreased to approximately 20 thousand ton in early 2020 is projected to recover to approximately 40 thousand ton in the 2020s and 2040s, followed by an incremental decline by 2060.

• Proceedings of the Korean Society of Crop Science Conference
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• 2018.04a
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• pp.35-35
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• 2018

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.07a
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• pp.205-213
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• 1999

밤의 세계 생산량은 1970 년대 연평균 약 45만 톤에서 1980 년대에 50만 톤으로 증가하였으며, 1990 년대에는 약 45만 톤을 유지하고 있다. 주요 생산국으로는 우리나라를 비롯해 중국, 터키, 이탈리아 등이며, 생산된 물량이 세계 전체 생산량의 약 75%를 차지하고 있다. 1995 년도 기준으로 국가별 생산현황은 중국이 24%, 터키 17%, 이탈리아 16%, 일본이 7%를 차지하고 있으며, 우리나라는 세계 제 2위의 생산국으로 93,655 톤을 생산하여 세계 생산량의 20%를 차지하고 있다. 밤은 국내에서 단일 농산물로서는 수출이 가장 많은 작물로서 1971 연도이래 꾸준히 증가하여 1996 년도에는 29,450톤을 수출하여 수출액이 1억1천2백만불을 달성하는 높은 실적을 나타냈다. (중략)

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.179-179
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• 2020

최근 관개배수를 위한 배수로의 활용범위는 농경지의 농업용수 공급과 더불어 농어촌 지역의 전기생산량 확보 등 다양한 방면에서 원활한 연구가 진행 중에 있다. 그 중 배수로 내부에 수차의 설치를 연계한 전기에너지 확보는 중소기업들을 대상으로 다양한 수차의 형상과 가동기법 등이 제시되고 있으며, 그 실효성에 대한 실험적 연구가 대두되고 있는 실정이다. 본 연구는 수류의 진행에 따라 양 방향으로 수차의 날개 회전이 가능한 양뱡향 수력발전기의 효율적인 운용 유·무 검토를 위하여 배수로 내 수심 및 유속 변화를 적용한 수리실험(원형실험)을 수행하였다. 또한, 실험 조건에 따른 수력발전기의 전기에너지 생산량을 예측하였다. 실험결과 수력발전기의 날개 면이 물과 접하는 최대 흘수심 구간에서 수차의 회전은 최대가속의 양상을 나타내었으며, 전기생산량은 날개 면의 흘수심이 감소함에 따라 비례적으로 낮게 측정되었다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.6
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• pp.545-550
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• 2012

Wind resource assessment is necessary when designing wind farm. To get the assessment, we must use a long term(20 years) observed wind data but it is so hard. so that we usually measured more than a year on the planned site. From the wind data, we can calculate wind energy related with the wind farm site. However, it calculate wind energy to collect the long term data from Met-mast(Meteorology Mast) station on the site since the Met-mast is unstable from strong wind such as Typhoon or storm surge which is Non-periodic. To solve the lack of the long term data of the site, we usually derive new data from the long term observed data of AWS(Automatic Weather Station) around the wind farm area using mathematical interpolation method. The interpolation method is called MCP(Measure-Correlative-Predict). In this study, based on the MCP Regression Model proposed by us, we estimated the wind energy at Handong site using AEP(Annual Energy Production) from Gujwa AWS data in Jeju. The calculated wind energy at Handong was shown a good agreement between the predicted and the measured results based on the linear regression MCP. Short term AEP was about 7,475MW/year. Long term AEP was about 7,205MW/year. it showed an 3.6% of annual prediction different. It represents difference of 271MW in annual energy production. In comparison with 20years, it shows difference of 5,420MW, and this is about 9 months of energy production. From the results, we found that the proposed linear regression MCP method was very reasonable to estimate the wind resource of wind farm.

• Environmental and Resource Economics Review
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• v.16 no.1
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• pp.27-63
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• 2007

Using the CGE model, this paper investigates economic impacts of a shortage in crude oil resulting from voluntary export restraints, OPEC's agreement of a cut in oil production, and/or a storing on speculation. Unlike most previous studies considering oil price as the unpredictable variable, this study constructs the model to determine the oil price endogenously under the condition of an insufficient supply of crude oil. According to IEA's extraordinary steps for a shortage of crude oil, we investigate an economic impact of 7~12% shortage below the level of business as usual. The results show that oil price soars by 17.3~33.5%, the rate of economic growth falls by 0.52~0.96%p, and the consumer price index(CPI) rises by 0.8~1.51%p. These results imply that increasing in 1%p of oil price results in decreasing in 0.03%p of economic growth and increasing in 0.045%p of consumer price index. The production of electricity declines because of the increase in production cost. A shortage of crude oil has an effect on sources of electricity. Most reduction in electricity generation occurs from the reduction in the thermal power generation which is highly dependent on crude oil. The shortage of crude oil causes demand for petroleum to significantly decline but demand for coal and heat to increase because of the substitution effect with petroleum. Demand for gas rise in the first year but falls from the second year.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.166-174
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• 2018

Potato(Solanum tuberosum L.) is one of the major food crop in the world following rice, wheat, and maize. It is thus important to project yield predict of potato under climate change conditions for assessment of food security. A crop growth modelling is widely used to simulate crop growth condition and total yield of various crops under a given climate condition. The decision support system for agrotechnology transfer (DSSAT) cropping system model, which was developed by U.S. which package integrating several models of 27 different crops, have been used to project crop yield for the impact assessment of climate change on crop production. In this study, we simulated potato yield using RCP 8.5 climate change scenario data, as inputs to the DSSAT model in five regions of Korea. The genetic coefficients of potato cultivar for 'superior', which is one of the most widely cultivated potato variety in Korea were determined. The GenCalc program, which is a submodule of the DSSAT package, was used to determine the genetic coefficients for the superior cultivar. The values of genetic coefficients were validated using results of 39 experiments performed over seven years in five regions. As a case study, the potato yield was projected that total yields of potato across five regions would increase by 26% in 2050s but decrease by 17% in 2090s, compared with 2010s. These results suggested that the needs for cultivation and irrigation technologies would be considerably large for planning and implementation of climate change adaptation for potato production in Korea.