• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.17-37
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• 1987

The purpose of this study is to establish more rational and practical planning theory for amusement park. It analyze and consider the fluctuation of people who come and use the Tong-Ch'on amusement park. The results drawn from this reserch work are as follows; 1. The main visitors of the Tong-Ch'on amusement park are students in their twenties and thirties, and people whose incomes are below 300,000 Won a month. The purpose of visit is for a rest rather than for amusement and user prefer summer, while the user is so rare in wintertime. Those phenomena observed are somewhat different from the real purpose of a amusement park which is on purpose to make profits by offering entertainments to the users. So planner should pay attention to the three points. They are varieties, seasonable diversification and fantastic character of facilties, in the amusement park. 2. The access time of the Tong-Ch'on amusement park was 41 minutes, the use frequency was 4 times a year and resident time was 164 minutes. The relationship of the three factors are as follows; log Y(F) =1.7832-0.0277(A.T) R$^2$=0.75 Y(R. F)=31.8885+3.3217(A.T) R$^2$=0.53 Y(R. T)=224.8959-87.8309 1og(F) R$^2$=0.38 F;Use frequency(time/year) A.T;Access Time(minute) R.T;Resident Time(minute) 3. In the choice of space, there were much differences according to tole user's age, job, degree of education, companion type and purpose of use. 4. There are considerable correlation between use fluctuation and some factors. The factors are season(summer, winter) as a time, temperature, cloud amount, duration of sunshine, weather(rainy-day) as a climate and a day of the week(weekday, holiday) as a social system. The important variables are temperature, cloud amount, duration of sunshine and a day of the week(weekday, holiday) to estimate the user of amusementpark. 5. 1 can reduce the following two types of regression models. 1) log$\sub$e/ Y1 = 6.9114 + 0.l135 TEM + 0.00002 SUN -0.4068W1 + 0.4316 W3 (R$^2$= 0.94) 2) log$\sub$e/ Y2 = 7.2069 + 0.l177 TEM - 0.0990 CLO + 0.4880 W3 (R$^2$=0.95) Y; Number of User TEM; Temperature CLO; Amount of cloud SUN; Duration of Sunshine W1; Weekday W3; Holiday Those model is in order to estimate the user for management of Tong-Ch'on amusement park and use on the computation of facility sloe for reconstruction. Besides the amusement park, city park and outdoor recreation area could estimate of user through this method. But, I am not sure about the regression models because I did not apply the regression models to the other amusement park, city Park or outdoor recreation area. Therefore, I think that this problem needs to be studied on in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.232-237
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• 2010

While global solar radiation is an essential input variable in crop models, the observation stations are relatively sparse compared with other meteorological elements. Instead of using measured solar radiation, the Angstrom-Prescott model estimates have been widely used. Monthly data for solar radiation and sunshine duration are a convenient basis for deriving Angstrom-Prescott coefficients (a, b), but it is uncertain whether daily solar radiation could be estimated with a sufficient accuracy by the monthly data - derived coefficients. We derived the Angstrom-Prescott coefficients from the 25 years observed global solar radiation and sunshine duration data at 18 locations across South Korea. In order to figure out any improvements in estimating daily solar radiation by replacing monthly data with daily data, the coefficients (a, b) for each month were derived separately from daily data and monthly data. Local coefficients for eight validation sites were extracted from the spatially interpolated maps of the coefficients and used to estimate daily solar radiation from September 2008 to August 2009 when, pyranometers were operated at the same sites for validation purpose. Comparison with the measured radiation showed a better performance of the daily data - derived coefficients in estimating daily global solar radiation than the monthly data - derived coefficients, showing 9.3% decrease in the root mean square error (RMSE).

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.409-419
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• 2010

In this study, for the purpose of analyzing the characteristics of Korean hydrologic weather parameters, 9 hydrologic weather parameters data such as annual precipitation, annual rainy days, annual average relative humidity, annual average temperature, annual duration of sunshine, annual evaporation, annual duration of precipitation, annual snowy days and annual new snowy days are collected from 63 domestic meteorological stations that has the hydrologic weather parameters records more than 30 years. And the basic characteristics of hydrologic weather parameters through basic statistics, moving average and linear regression analysis are perceived. Also trend using the statistical methods like Hotelling-Pabst test and Mann-Kendall test about hydrologic weather parameters is analyzed. Through results of basic analysis, moving average and linear regression analysis it is shown that precipitation is concentrated in summer and deviation of precipitation for each season showed significant difference in accordance with Korean climate characteristics, besides the increase in annual precipitation and annual average temperature, annual average relative humidity and annual duration of sunshine reduction and annual rainy days is said to increase or decrease. The results of statistical analysis of trend are summarized as trend commonly appeared in annual average relative humidity and annual average temperature. and annual precipitation, annual rainy days and annual duration of sunshine showed different results according to area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.926-932
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• 2004

This study deals with the statistical analyses on the relationship between the red tide formation and the meteorological factors in the Korean coastal waters. From 1995 to 2002, the red tide was observed every year and the number of occurrences increased as well. The red tide mostly occurred in July, August, September and October. from multiple linear regression, the meteorological factors governing the mechanisms of the increase in the number of red tide occurrences are found to be a water temperature, rainfall, sunshine duration and wind velocity. But water temperature as the limited factor controlling the growth of phytoplankton (Cochlodinium polykrikoids) in 15∼$30^{\circ}c$. NO ＝ 8.089 - 0.319WT + 0.019RF + 0.141SD + 0.l19WV (R ＝ 0.897) in August NO = 7.531 - 0.327WT + 0.027RF + 0.208SD + 0.208WV (R ＝ 0.894) in September Here, NO is the number of occurrence for red tide, WT is water temperature, RF is rainfall, SD is sunshine duration and WV is wind velocity, respectively. The necessary times till the day of red tide occurrence verse the day when water temperature reaches $15^{\circ}c$ are 78∼104 days, then it should be divided the coastal waters into 4 areas by the comparison among the accumulated sunshine duration, water temperature and rainfall as follows； the South West Coast (SW), South Middle Coast (SM), South East Coast(SE) and East South Coast (ES). The coastal areas that red tide occurs were complicated and various by change of marine environments. Usually red tide with a high concentrations (individual number, cells/ml) appeared in SM and SE. It was found that the general situations for the frequencies of red tide formation are mainly concentrated to 24.5∼$25^{\circ}c$ (high water temperature) and eve. 1000 cells/ml (high individual number) such as the category of red tide warning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.782-785
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• 2011

Needs for MG(Microgrid) development are increasing all over the world as a solution to the problems including the depletion problem of energy resources, the growing demand for electric power and the climatic and environmental change. Especially Photovoltaic power is one of the most general renewable energy resources. However there is a problem of the uniformity of power quality because the power generated from solar light is very sensitive to climate fluctuation (variation of insolation and duration of sunshine, etc). As a solution to the above problem, ESS(Energy Storage System) is considered generally, but it has some limitations. To solve this problem this paper suggests a hybrid estimation method of photovoltaic power generation according to two climatic factors, i.e. insolation and sunshine. This result seems to help design the appropriate capacity of ESS and estimate the proper switching time between DC and AC power in the premises power system and thus maintain the uniformity of power quality.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.766-770
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• 2005

Cascade-Correlation Neural Networks Model(CCNNM) is used to estimate daily evaporation using limited climatical variables such as atmospheric temperature, dewpoint temperature, relative humidity, wind speed, sunshine duration and radiation. DeBruln equation is applied to estimate daily free-surface evaporation. It is converted into pan evaporation using pan coefficient. The results of CCNNM shows better than those of Debruin equation. This research represents that the strong nonlinear relationship such as evaporation modeling can be generalized by the CCNNM ; a special type of Backpropagation algorithm Neural Networks Model.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.5-8
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• 2002

Daily potential evapotranspiration was estimated using meteorological data which are observing regularly such as rainfall, temperature, humidity, wind speed, and duration of sunshine. Penman method is used practically in estimating evapotranspiration at present, and its regional coefficients were derived at 19 stations in the Korean Peninsular. Because meteorological data are observing at 77 stations under the Korea Meteorological Administration, the methodology of estimating evapotranspiration using meteorological data will be able to be applied in more regions than Penman method.

• Korean System Dynamics Review
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• v.2 no.1
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• pp.51-68
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• 2001

Politicians are competing to persuade their policies and to oppose other's. Policy persuasion is based on two independent reasons; moral causes vs. economic outcomes. There have been few studies on investigating and comparing their structural differences. This paper studies how policy makers use moral causes and economic outcomes in persuading their policies. Causal and cognitive structures of persuasions for and against sunshine policy are compared by cognitive map analysis. Finally, this study discusses how to use causal map analysis to understand moral causes and economic outcomes as tools for policy persuasion.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.146-156
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• 2010

The objective of this study was to improve the accuracy of calculation and estimation of solar radiation and duration of sunshine, which are the most important variables of photovoltaic power generation in deciding the location of photovoltaic facilities efficiently. With increasing interest in new and renewable energies, research on solar energy is also being conducted actively, but there have not been many studies on the location of photovoltaic facilities. Thus, this study calculated solar duration and solar radiation based on geographical factors, which have the most significant effect on solar energy in GIS environment, and corrected the results of analysis using diffuse radiation. Moreover, we performed ordinary kriging, a spatial statistical analysis method, for estimating values for parts deviating from the spatial resolution of input data, and used variogram, which can determine the spatial interrelation and continuity of data, in order to estimate accurate values. In the course, we compared the values of variogram factors and estimates from applicable variogram models, and selected the model with the lowest error rate. This method is considered helpful to accurate decision making on the location of photovoltaic facilities.

• The Research Journal of the Costume Culture
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• v.25 no.2
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• pp.117-129
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• 2017

The purpose of this study was to investigate meteorological factors' effects on clothing sales based on empirical data from a leading apparel company. The daily sales data were aggregated from "A" company's store records for the Fall/Winter season from 2012 to 2015. Daily weather data corresponding to sales volume data were collected from the Korea Meteorological Administration. The weekend effect and meteorological factors including temperature, wind, humidity, rainfall, fine dust, sea level pressure, and sunshine hours were selected as independent variables to calculate their effects on A company's apparel sales volume. The analysis used a SAS program including correlation analysis, t-test, and multiple-regression analysis. The study results were: First, the weekend effect was the most influential factor affecting sales volume, followed by fine dust and temperature. Second, there were significant differences in the independent variables'effects on sales volume according to the garments' classification. Third, temperature significantly affected outer garments'sales volume, while top garments' sales volume was not influenced significantly. Fourth, humidity, sea level pressure and sunshine affected sales volume partly according to the garments' item. This study can provide proof of significant relationships between meteorological factors and the sales volume of garments, which will serve well to establish better inventory strategies.