• Journal of Energy Engineering
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• v.17 no.1
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• pp.31-37
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• 2008

At present, the target amount of demand-side management and investment cost of EE (Energy Efficiency) program, which consists of high-efficiency appliances, has been estimated simply by the diffusion function based on the real historical data in the past or last year. In the internal and external condition, the penetration amount of each appliance has been estimated by Bass diffusion model which is expressed by time and three coefficients. And enough acquisition of real historical data is necessary for reasonable estimation of coefficients. In energy efficiency, to estimate the target amount of demand-side management, the penetration amount of each appliance should be primarily forecasted by Bass diffusion model in Korea. On going programs, however, lightings, inverters, vending machine and motors have a insufficient real historical data which is a essential condition to forecast the penetration amount using a Bass diffusion model due to the short period of program progress. In other words, the forecast of penetration amount may not be exact, so that it is necessary for the method of forecast to apply improvement of method. In this paper, the penetration amount of high-efficiency appliances is forecasted by Bass, virtual Bass, Logistic and Lawrence & Lawton diffusion models to analyze the diffusion progress. And also, by statistic standards, each penetration is compared with historical data for model suitability by characteristic of each appliance. Based on the these result, in the forecast of penetration amount by diffusion model, the reason for error occurrence caused by simple application of diffusion model and preferences of each diffusion model far a characteristic of data are analyzed.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.295-299
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• 2001

To protect the flooding damages in Medium and Small watershed, it needs to set up flood warning system and develope Flood forecasting Model in real-time basis for medium and small watershed. In this study, it was able to minimize the error range between forecasted flood inflow and actual flood inflow, and forecast accurately the flood discharge some hours in advance by using simplex method recursively for the determination of the best parameters of RETFLO model. The result of RETFLO performance applied to several storm of Yugu river during 3 past years was very good with relative errors of 10% for comparison of total runoff volume and with one hour delayed peak time.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.42-58
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• 2008

Nowadays the installation of Real-time Traffic Signal Control system is gradually spread, in order to solve the traffic problem which become serious. The most important thing are reliability of data collection and functionality of system in Real-time Traffic Signal Control System. But, the evaluation for those introduction system are defective after system constructing. So, many systems are not working properly to those systems's primarily purpose. This study is executed expansion through field test and analysis which check performance and advise of system operation. It has purpose to establish of the maintenance system of Real-time Traffic Signal Control system. As the result of analysis, we could find the several problems in this study. So, we also could guess that the effective maintenance systems of the Real-time Traffic Signal Control system is necessary within few years.

• East Asian Economic Review
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• v.22 no.3
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• pp.371-400
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• 2018

Although asset price is an important factor in determining changes in external balances, no studies have investigated it from the Chinese perspective. In this study, I empirically examine the underlying driving forces of China's trade balances, particularly the role of asset price and the real exchange rate. To this end, I estimate a sign-restricted structural vector autoregressive model with quarterly time series data for China, using the Bayesian method. The results show that changes in asset price affect China's trade balances through private consumption and investment. Also, an appreciation of the real exchange rate tends to deteriorate trade balances in China. Furthermore, forecast error variance decomposition results indicate that changes in asset price (stock price and housing price) explain about 20% variability of trade balances, while changes in the real exchange rate can explain about 10%.

• Journal of the Korea Computer Industry Society
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• v.6 no.2
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• pp.241-248
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• 2005

Conventional estimating methods forecast the future that it usually using the past statistical numerical value. In order to forecast the farming price, it must need many effort and accuracy knowledge. Therefore, to solve the these problems, this paper to improve forecasting farming price using fuzzy rules and neural network as a preprocessing. Also, we developed an intelligent farming expert system for real time forecasting as a postprocessing about unexpectable conditions. Computer simulation results proved reducing pricing error which proposed farming price expecting system better than conventional demand forecasting system does not using fuzzy rules.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.535-538
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• 2003

A Grey model was developed to forecast short-term runoff from the Naju watershed in Korea. In calibration, the root mean square error(RMSE) of the simulated runoff of six hours ahead using Grey model ranged from 6.3 to $290.52m^3/s,\;R^2$ ranged from 0.91 to 0.99, compared to the observed data. In verification, the RMSE ranged from 75.7 to $218.9m^3/s,\;R^2$ ranged from 0.87 to 0.96, compared to the observed data. The results in this study demonstrate that the proposed model can reasonably forecast runoff one to six hours ahead.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.311-324
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• 2021

Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.

• Atmosphere
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• v.17 no.1
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• pp.69-86
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• 2007

The characteristics of the dual-Doppler wind retrieval method based on a three dimensional variational (3DVAR) conception were investigated from the following four points of view; the sensitivity of the number of iteration, the effect of the weak constraint term, the effect of the smoothness term, and the sensitivity of the error mixing ratio of the radial velocities. In the experiment, the radial velocities relative to the Gosan and Jindo radar sites of the Korea Meteorological Administration (KMA) were calculated from the forecasting of the WRF (Weather Research and Forecast; Skamarock, 2004) model at 1330 UTC 30 June 2006, which is the one and half hour forecast from the initial time, 1200 UTC on that day. The results showed that the retrieval performance of the horizontal wind field was robust, but that of the vertical wind was sensitive to the external conditions, such as iteration number and the on/off of the weak constraint term. The sensitivity of error mixing ratio was so large that even the horizontal wind retrieval efficiency was reduced a lot. But the sensitivity of the smooth term was not so large. When we applied this method to the real mesoscale convective system (MCS) between the Gosan and Jindo radar pair at 1430 UTC 30 June 2006, the wind structure of the convective cells in the MCS was consistently retrieved relative to the reflectivity factor structure. By comparing the vertical wind structure of this case with that of 10 minutes after, 1440 UTC 30 June 2006, we got the physical consistency of our method.

• Atmosphere
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• v.22 no.2
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• pp.233-243
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• 2012

The Barnes scheme is used in Digital Forecast System (DFS) of the Korea Meteorological Administration (KMA) for real-time analysis. This scheme is an objective analysis scheme with a distance-dependent weighted average. It has been widely used for mesoscale analyses in limited geographic areas. The isotropic Gaussian weight function with a constant effective radius might not be suitable for certain conditions. In particular, the analysis error can be increased for stations located near mountains. The terrain of South Korea is covered with mountains and wide plains that are between successive mountain ranges. Thus, it is needed to consider the terrain effect with the information of elevations for each station. In order to improve the accuracy of the temperature objective analysis, we modified the weight function which is dependent on a distance and elevation in the Barnes scheme. We compared the results from the Barnes scheme used in the DFS (referred to CTL) with the new scheme (referred to EXP) during a year of 2009 in this study. The analysis error of the temperature field was verified by the root-mean-square-error (RMSE), mean error (ME), and Priestley skill score (PSS) at the DFS observation stations which is not used in objective analysis. The verification result shows that the RMSE and ME values are 1.68 and -0.41 in CTL and 1.42 and -0.16 in EXP, respectively. In aspect of spatial verification, we found that the RSME and ME values of EXP decreased in the vicinity of Jirisan (Mt. Jiri) and Taebaek Mountains. This indicates that the new scheme performed better in temperature verification during the year 2009 than the previous scheme.