• Korean Journal of Ecology and Environment
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• v.49 no.2
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• pp.142-146
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• 2016

The purpose of this study is to evaluate topographic characteristics revealed in the predicted distribution areas of Aporia crataegi, according to climate change. Towards this end, this study compared the differences of topographic factors, such as altitude, mountain slope and the aspect of slope, in the distribution areas with different potential inhabitation possibilities of the Aporia crataegi. The inhabitation possibilities of the Aporia crataegi were different, according to altitude and topographic slope, and the inhabitation possibility is judged to be affected more by the topographic conditions including altitude and mountain slope than by the aspect of slope. Especially, the inhabitation possibility of the Aporia crataegi was higher in the higher altitude area, as time goes on furthermore. The reason is that the current climate environment, which is suitable for the potential inhabitation of the Aporia crataegi, is forecast to be formed with an area with high altitude. Although the difference in the aspect of slope was not statistically significant according to inhabitation possibility, the reason why the inhabitation possibility of the Aporia crataegi varies in the mainly southeast slope is conjectured to be derived from the warmer heat environmental condition to grow from a larva into an imago. The result drawn in this study is expected to be utilized as basic data to establish a policy soundly preserving and managing the habitat of biospecies in consideration of climate change and topographic conditions in the natural ecosystem field by using the already built up various biological resources information.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.119-133
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• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.198-210
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• 2016

This study firstly aims to estimate a leading-price of Jeju flounders with various price-classes by fish weight and secondly plans to provide policy implications of flounder purchase projects by understanding dynamic changes and interactions among flounder producer price-classes caused by price impulses in the market. This study applies an unit root test for stability of data, uses a Granger causality test to estimate the leading-price among producer prices by fish weight, employs the vector autoregressive model to analyze statistical impacts among t-1 variables used in models, and finally utilizes impulse response analyses and forecast error variance decomposition analyses to understand dynamic changes and interactions among change rates of the producer prices caused by price impulses in the market. The results of the study are as follows. Firstly, KPSS, PP, and ADF tests show that the change rate of Jeju flounder monthly producer prices by fish weight differentiated by logarithm is stable. Secondly, the Granger causality test presents that the change rate of the 1kg flounder producer price strongly leads it of 500g, 700g, and 2kg flounder producer prices respectively. Thirdly, the vector autoregressive model indicates that the change rate of the 1kg producer price in t-1 period statistically, significantly influences it of own weight in t period and also slightly affects price change rates of other weights in t period. Fourthly, the impulse response analysis indicates that impulse responses of structural shocks for the change rate of the 1kg producer price are relatively more powerful in its own weight and in other weights than shocks emanating from price change rates of other weights. Fifthly, the variance decomposition analysis points out that the change rate of the 1kg producer price is relatively more influential than it of 500g, 700g, and 2kg producer prices respectively. In conclusion, the change rate of the 1kg Jeju flounder producer price leads the change rates of other ones and Jeju purchase projects need to be targeted to the 1kg Jeju flounder producer price as the purchase project implemented in 2014.

• Korean Security Journal
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• no.19
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• pp.1-21
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• 2009

Manpower demand forecasting in private security industry can be used for both policy and information function. At a time when police agencies have fewer resources to accomplish their goals, forming partnership with private security firms should be a viable means to choose. But without precise understanding of each other, their partnership could be superficial. At the same time, an important debate is coming out whether security industry will continue to expand in numbers of employees, or level-off in the near future. Such debates are especially important for young people considering careers in private security industry. Recently, ARIMA model has been widely used as a reliable instrument in the many field of industry for demand forecasting. An ARIMA model predicts a value in a response time series as a linear combination of its own past values, past errors, and current and past values of other time series. This study conducts a short-term forecast of manpower demand in private security industry using ARIMA model. After obtaining yearly data of private security officers from 1976 to 2008, this paper are forecasting future trends and proposing some policy orientations. The result shows that ARIMA(0, 2, 1) model is the most appropriate one and forecasts a minimum of 137,387 to maximum 190,124 private security officers will be needed in 2013. The conclusions discuss some implications and predictable changes in policing and coping strategies public police and private security can take.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.113-123
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• 2011

Recently, the global warming problem has arised around world, many nations has set up a various regulations for decreasing $CO_2$. In particular, $CO_2$ emissions reduction effect is very powerful in transport part, so there is a rising interest about development of green car, or electric vehicle in auto industry. For this reason, it is important to make a strategy for charging infra and forcast electric power demand, but it hasn't introduced about demand forecasting electric vehicle. Thus, this paper presents a demand forecasting for electric vehicles using choice based multigeneration diffusion model. In this paper, it estimates innovation coefficient, immitation coefficient in Bass model by using hybrid car market data and forecast electric vehicle market by year using potential demand market through SP(Stated Preference) experiment. Also, It facilitates more accurate demand forecasting electric vehicle market refelcting multigeneration diffusion model in accordance with attribute progress in development of electric vehicle. Through demand forecasting methodology in this paper, it can be utilized power supply and building a charging infra in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.9-23
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• 2002

The purpose of this research was to develop a model that minimizes time and money for deriving topographical property factors and hydro-meteorological property factors, which are used in interpreting flood flow, and that makes it possible to forecast rainfall-runoff using a least number of factors. That is, the research aimed at suggesting a runoff interpretation method that considers the river branching characteristics but not the topographical and geological properties and the land cover conditions, which had been referred in general. The subject basin of the research was the basin of Yeongcheon Dam located in the upper reaches of the Kumho River. The parameters of the model were derived from the results of abstracting topological properties out of rainfall-runoff observation data about heavy rains and Digital Elevation Modeling(DEM). According to the result of examining calculated peak runoff, the Clark Model and the GIUH Model showed relative errors of 1.9~23.9% and 0.8~11.3%, respectively and as a whole, the peak values of hydrograph appeared high. In addition, according to the result of examining the time when peak runoff took place, the relative errors of the Clark Model and the GIUH Model were 0.5~1 and 0~1 hour respectively, and as a whole, peak flood time calculated by the GIUH Model appeared later than that calculated by the traditional Clark Model.

• Journal of Environmental Science International
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• v.19 no.4
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• pp.415-425
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• 2010

The purpose of the present study was to analyze the vegetation structure and distributional characteristics of Abies koreana forests in Mt. Halla, and to provide basicdata for an ecological study on Abies koreana in Mt. Halla. The results of the analysis showed that the mean importance percentage(M.I.P,) of Abies koreana in the Youngsil and Bangaeoreum and the Azalea field were 28.3%, 23.6%, and 46.4%, respectively. The ratios of DBH (diameter at breast height) to height were similar in all region, except in the Azalea field, where Abies koreana of various ages, both young and old, were found. The species diversity (H) of the upper and lower layers in the Youngsil and Bangaeoreum and in the Azalea field were 0.625 and 0.810, 0.731 and 0.848, and 0.342 and 0.757, respectively. A total of 52 community were distributed at locations higher than 1,300m above sea level. The proportions of each community in the whole Abies koreana forest were 56.5%(Azalea field), 11.0% (Youngsil trail at 1,550-1,650 m above sea level), and 8.1%(Janggumok and Kundurewat region). The total area of the Abies koreana forest was calculated to be 795.3ha by combining all the areas of each community. An Abies koreana forest with the largest area was found at locations 1,500-1,600 m above sea level, taking up 38.8% of the total Abies koreana forest area. For the slopes of the distributional area of Abies koreana, 46.1%(highest proportion) of the total area was $10\sim25^{\circ}$, and for the azimuth of the distributional area, 17.4%(the highest proportion) of the total area was $0-45^{\circ}$. The vegetation structure showed large differences between areas. It was found, however, that the distribution was mostly in the areas with a relatively gentle slope. It is suggested that research be done to forecast the possible changes in the differences in the vegetation structures between different areas caused by climate changes. In addition, there is a need to monitor the Abies koreana and alpine plants in the subalpine zones of Mt. Halla, which are sensitive to climate change, to obtain the basic data that are necessary for the protection and maintenance of the ecosystem.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.1
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• pp.59-65
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• 2010

The purpose of this study is to analyze the risk of the forest fire, considering the topography and the forest, for establishing disaster prevention measures of cultural heritage, Uireung, over in Cheonjang-mountain. To do that, we estimate the occurrence and spread of the forest fire over in Cheonjang-mountain through a forest fire probability model(logistic regression), using the space characteristic data($100m{\times}100m$). The factor, occurrence of the forest fire, are diameter class, southeast, southwest, south, coniferous, deciduous, and mixed forest. We assume the probability of the fire forest in each point as follow : [1+exp{-(-4.8081-(0.02453*diameter class)+(0.6608*southeast)+(0.507*southwest)+(0.7943*south)+(0.29498*coniferous forest)+(0.28897*deciduous forest)+(0.17788*mixed forest))}]$^{-1}$. To divide dangerous zone of the big forest fire, we make the basic materials for disaster prevention measures, through the map of coniferous forests, deciduous forests, and mixed forest. The damage of cultural heritage caused by a forest fire will be reduced through the effective preventive measures, by forecast a forest fire to using this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.3
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• pp.127-137
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• 1992

For the real-time control of a multi-purpose reservoir in case of a storm, it is absolutely necessary to forecast accurate flood inflows through a good rainfall-runoff model by calibrating the parameters with the on-line rainfall and water level data transmitted by the telemetering systems. To calibrate the parameters of a runoff model. the trial and error method of manual calibration has been adopted from the subjective view point of a model user. The object of this study is to develop a automatic calibration method using an optimization technique. The pattern-search algorithm was applied as an optimization technique because of the stability of the solution under various conditions. The object function was selected as the sum of the squares of differences between observed and fitted ordinates of the hydrograph. Two historical flood events were applied to verify the developed technique for the automatic calibration of the parameters of the storage-function rainfall-runoff model which has been used for the flood control of the Soyanggang multi-purpose reservoir by the Korea Water Resources Corporation. The developed method was verified to be much more suitable than the manual method in flood forecasting and real-time reservoir controlling because it saves calibration time and efforts in addition to the better flood forecasting capability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.137-145
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• 2012

According to the National Police Agency, the total number of traffic accidents which occurred in 2010 was 226,878. Intersection accidents accounts for 44.8%, the largest portion of the entire traffic accidents. An research on the signalized intersection is constantly made, while an research on the unsignalized intersection is yet insufficient. This study selected traffic volume, road width, and sight distance as the input variables which affect unsignalized intersection accidents, and number of accidents as the output variable to build a model using ANFIS(Adaptive Neuro-Fuzzy Inference System). The forecast performance of this model is evaluated by comparing the actual measurement value with the forecasted value. The compatibility is evaluated by R2, the coefficient of determination, along with Mean Absolute Error (MAE) and Mean Square Error (MSE), the indicators which represent the degree of error and distribution. The result shows that the $R^2$ is 0.9817, while MAE and MSE are 0.4773 and 0.3037 respectively, which means that the explanatory power of the model is quite decent. This study is expected to provide the basic data for establishment of safety measure for unsignalized intersection and the improvement of traffic accidents.