• Korean Journal of Agricultural Science
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• v.38 no.3
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• pp.571-581
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• 2011

This study develops a mid-term preceding observation model of radish to complement an existing short-term agricultural observation model. The first purpose of the study is to extend a three seasonal classification(spring, summer, fall) of fruit-vegetables to a four seasonal classification that involves the winter additionally. This allows us to verify the reason for demand and supply unbalance and unstable price of radish. The second purpose is to construct a mid-term preceding observation model that would be used to forecast planted areas, output, monthly shipment and price. To achieve these purposes, several multiple regression models are estimated. A system is consisted of a planted areas equation, a yield equation, monthly shipment distribution equation, and monthly price equation. To calculate output an auxiliary equation is involved in the system and the consumer price index etc are considered as exogenous variables.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.178-178
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• 2022

• Journal of Distribution Science
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• v.14 no.11
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• pp.83-90
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• 2016

Purpose - During the last two years, convenient stores (CS) are emerging as one of the most fast-growing retail trades in Korea. The goal of this work is to forecast and to analyze sales at CS using ARIMA-Intervention model (IM) and exponential smoothing method (ESM), together with sales at supermarkets in South Korea. Considering that two retail trades above are homogeneous and comparable in size and purchasing items on off-line distribution channel, individual behavior and characteristic can be detected and also relative superiority of future growth can be forecasted. In particular, the rapid growth of sales at CS is regarded as an everlasting external event, or step intervention, so that IM with season variation can be examined. At the same time, Winters ESM can be investigated as an alternative to seasonal ARIMA-IM, on the assumption that the underlying series shows exponentially decreasing weights over time. In case of sales at supermarkets, the marked intervention could not be found over the underlying periods, so that only Winters ESM is considered. Research Design, Data, and Methodology - The dataset of this research is obtained from Korean Statistical Information Service (1/2010~7/2016) and Survey of Service Trend of Korea Statistics Administration. This work is exploited time series analyses such as IM, ESM and model-fitting statistics by using TSPLOT, TSMODEL, EXSMOOTH, ARIMA and MODELFIT procedures in SPSS 23.0. Results - By applying seasonal ARIMA-Intervention model to sales at CS, the steep and persisting increase can be expected over the next one year. On the other hand, we expect the rate of sales growth of supermarkets to be lagging and tied up constantly in the next 2016 year. Conclusions - Based on 2017 one-year sales forecasts for CS and supermarkets, we can yield the useful information for the development of CS and also for all retail trades. Future study is needed to analyze sales of popular items individually such as tobacco, banana milk, soju and so on and to get segmented results. Furthermore, we can expand sales forecasts to other retail trades such as department stores, hypermarkets, non-store retailing, so that comprehensive diagnostics can be delivered in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.187-194
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• 2019

Traditional demand forecasting methods are difficult to meet the needs of companies due to rapid changes in the market and the diversification of individual consumer needs. In a diversified production environment, the right demand forecast is an important factor for smooth yield management. Many of the existing predictive models commonly used in industry today are limited in function by little. The proposed model is designed to overcome these limitations, taking into account the part where each model performs better individually. In this paper, variables are extracted through Gray Relational analysis suitable for dynamic process analysis, and statistically predicted data is generated that includes characteristics of historical demand data produced through ARIMA forecasts. In combination with the LSTM model, demand forecasts can then be calculated by reflecting the many factors that affect demand forecast through an architecture that is structured to avoid the long-term dependency problems that the neural network model has.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• Structural Engineering and Mechanics
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• v.85 no.2
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• pp.179-195
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• 2023

The performance of reinforced concrete (RC) beam specimens strengthened using a newly proposed Side Near Surface Mounted (S-NSM) technology was investigated experimentally in this work. In addition, analytical and nonlinear finite element (FE) modeling was exploited to forecast the performance of RC members reinforced with S-NSM utilizing steel bars. Five (one control and four strengthened) RC beams were evaluated for flexural performance under static loading conditions employing four-point bending loads. Experimental variables comprise different S-NSM reinforcement ratios. The constitutive models were applied for simulating the non-linear material characteristics of used concrete, major, and strengthening reinforcements. The failure load and mode, yield and ultimate strengths, deflection, strain, cracking behavior as well as ductility of the beams were evaluated and discussed. To cope with the flexural behavior of the tested beams, a 3D non-linear FE model was simulated. In parametric investigations, the influence of S-NSM reinforcement, the efficacy of the S-NSM procedure, and the structural response ductility are examined. The experimental, numerical, and analytical outcomes show good agreement. The results revealed a significant increase in yield and ultimate strengths as well as improved failure modes.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.23-30
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• 1998

The construction of the transportation history database system is to serve the scheduling and seat inventory controling. Recently, lots of countries have been faced with the advance era because of the new railway transportation system, like the high speed railway and/or magnetic levitation vehicle system. This can be reasonably translated as those of operators are willing to provide the more various and high quality schedule to the customer. Those operators' these ideas make possible to forecast that scheduling process is going to be complicated more and more The seat inventory control, so to speak Yield Management System(YMS), goes a long way to improve the total passenger revenue at the railway business. The YMS forecasts the number of the last reservation value(DCP# END) and recommends the optimal values on the seat sales. The history database system contains infra-data(ie, train, seat, sales) that will be the foundation of scheduling and seat inventory control application programs. The development of the application programs are reserved to the next step. The database system is installed on the pc platform(IBM compatible), using the DB2(RDBMS). And at next step, the platform and DBMS will be considered whether they can meet the users' requirement or not.

• Korean Journal of Agricultural Science
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• v.23 no.2
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• pp.285-300
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• 1996

This study is aimed to provide data of low-input rice cultivation for agricultural policy, to reveal the problems of low-input cultivation through comparing the economic result of low-input cultivation with the common one, to search for solution or mitigation of the problems of low-input cultivation, and to forecast the future prospect of low-input rice cultivation. The following were the results obtained from the survey and analysis. The working hours per 10a inputted 45.4 hours which is 32% more than 34.5 hours of common cultivation. Yield per 10a was 355kg which was 101kg less than 456kg of common cultivation. But the farm received price per kg was 1,984.9 won which was 547.9 won more than 1,436.5 won of common cultivation. Gross receipts per 10a was 704,438 won which was higher than 655,044 won of common cultivation, and management cost was 230,820 won which slightly higher than 188,157 won of common cultivation. Consequently, the income of low-input rice cultivation was 473,617 won which somewhat exceed to 466,887 won of common cultivation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.30 no.3
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• pp.259-270
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• 1985

Meteorological year variations for rice crop from 1973 to 1984 were compared by using air temperature and sunshine hour for nursery period, cooling index for reproductive stage and meteorological yield productivity index for ripening period. The most optimum transplanting date and heading date for crop yield based on real transplanting date-grain yield relationship or heading date-grain yield relationship, meteorological yield productivity index and actual results showed good agreement each other. Around May 26 for transplanting and August 10 for heading were the most optimum date in Indica/Japonica hybrid cultivars while these were about June 8 and August 23 for Japonica cultivars, respectively. On the other hand, theoretical late limiting heading date for safe ripening were August 20 for Indica/Japonica hybrid cultivars and August 30 for Japonica cultivars, respectively, for both methods, cumulative temperature method during ripening with 80% believable frequency and meteorological yield productive index method having 1000(kg/10a) yielding potential. Based on the yield forecast trial, the highest values of photosynthetic efficiency, 2.5%, and crop growth rate, 23g/㎡/day, were recorded during 30 days before rice heading. Considering the photosynthetic efficiency and solar radiation, the potential crop growth rate was more or less 30g/㎡/day and the biological grain yielding potential in a existing cultural practices was approximately 900-1000(kg/10a) in Milyang weather condition. To increase further yielding potential, either photosynthetic efficiency or harvest index or both should be improved by manipulating appropriate canopy architecture, plant spacing, fertilizer, chemical, etc.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.312-319
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• 2009

The purpose of the paper is to offer an analysis of adult probationers and their recidivism and to suggest a policy to prevent recidivism. Various data analysis methods like frequency analysis, cross-tabulation analysis, regression analysis and logistic regression analysis were used to determine which of a second offense factors and recidivism included in initial data investigation could effectively explain or forecast reference values. This study focused on identifying relations associated with follow-up misconducts of adults under probation, and supposing that those factors could be associated with their second offenses. But it failed to yield so much significant findings. Nevertheless, this study has its own significance in a sense that it explored various risk factors and desires of adults under probation according to empirical data, and suggested formulated measures useful in practice to select and categorize appropriate treatments.