• Journal of the Korean Institute of Gas
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• v.19 no.2
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• pp.20-28
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• 2015

A suitable monitoring method is necessary for successful policy implementation and its evaluation, required for effective prevention of abnormal fire occurrences. To do this, there were studies for applying control charts of quality management to fire occurrence monitoring. As a result, it was proved that more fire occurs in winter and its trend moves yearly-basis with some patterns. Although it has trend, if we apply the same criteria for each time, inefficient overreacting fire prevention policy will be accomplished in winter, and deficient policy will be accomplished in summer. Thus, applying different control limits adaptively for each time would enable better forecasting and monitoring of fire occurrences. In this study, we treat fire occurrences as time series model and propose a method for configuring its coefficients with ARIMA model. Based on this, we expect to carry out advanced analysis of fire occurrences and reasonable implementation of prevention activities.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.763-777
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• 2002

The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

• International Area Studies Review
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• v.16 no.1
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• pp.275-301
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• 2012

This study analyzes the regional disparity in India between 24 states over the period 1980 to 2009. The traditional regressive and spatial autoregressive models are used that includes measures of spatial effects. The results provide no evidence that convergence is valid in India. However, the results indicate that spatial interaction is an important element of state growth in India. The result of spatial analysis excluded two outliner states reveals more strong relationship between the weighted spatial income level and the state growth rates. Moreover, the results find that the coefficients of spatial lag of initial per capital and error terms are significantly negative. The coefficient of variation measures that the distribution of state income level has diverged over time. Therefore, this study concludes that the growth of regional state income does not have a tendency to converge rater than diverge. The results is rational because as the Indian economy is growing rapidly, some states grow faster than the others while initial poor states become the poorest ones, which increases regional disparity in India.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.73-85
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• 2006

Array observations of the vertical component of microtremors are frequently conducted to estimate a subsurface layered-earth structure on the assumption that microtremors consist predominantly of the fundamental mode Rayleigh waves. As a useful tool in the data collection, processing and analysis, the spatial autocorrelation (SPAC) method is widely used, which in practice requires a circle array consisting of M circumferential stations and one centre station (called "M-station circle array", where M is the number of stations). The present paper considers the minimum number of stations required for a circle array for efficient data collection in terms of analytical efficacy and field effort. This study first rearranges the theoretical background of the SPAC algorithm, in which the SPAC coefficient for a circle array with M infinite is solely expressed as the Bessel function, $J_0(rk)$ (r is the radius and k the wavenumber). Secondly, the SPAC coefficient including error terms independent of the microtremor energy field for an M-station circle array is analytically derived within a constraint for the wave direction across the array, and is numerically evaluated in respect of these error terms. The main results of the evaluation are: 1) that the 3-station circle array when compared with other 4-, 5-, and 9-station arrays is the most efficient and favourable for observation of microtremors if the SPAC coefficients are used up to a frequency at which the coefficient takes the first minimum value, and 2) that the Nyquist wavenumber is the most influential factor that determines the upper limit of the frequency range up to which the valid SPAC coefficient can be estimated.

• Management & Information Systems Review
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• v.37 no.3
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• pp.65-81
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• 2018

This study estimated the long-run and the short-run price and income elasticity of crude oil demand by using the ARDL model in Korea. First, the long-run cointegration relationship existed between crude oil demand and price or income in the ARDL-bounds tests. Second, the long-run own price, the cross price elasticity and the income elasticity were both statistically significant elastic and sensitive in the ARDL. Third, there was autocorrelation of the residuals, but no misspecification errors and heteroscedasticity, and then the residuals showed a normal distribution. And the CUSUM & CUSUMSQ tests showed that the coefficients were stable. Fourth, the short-run own price, the cross price elasticity and the income elasticity were both statistically significant elastic and sensitive in the ARDL-RECM. The ECM with the short-run dynamics showed rapid adjustments in the long-run equilibrium of oil demand after the economic crisis. In the short-run, the sensitivity of crude oil demand to price and income changes has moved in the same direction as the long-run case. Korea, depending too much on foreign crude oil, is vulnerable to the shocks of oil prices, so rising oil prices can certainly have a negative impact on Korea's trade balance. And the elasticity of long-run oil prices may help to control and manage Korea's oil demand. The government needs to strengthen monitoring of the country's policies and market trends related to crude oil, establish strategies to customize national policies and market conditions, and strengthen active market dominance efforts through pioneering new market and diversification.

• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.529-544
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• 2018

Dongrae hot spring belongs to the residual magma type and has a long history of bathing since the Silla dynasty in Korea. Due to long development of hot spring water, it is expected that the amount of hot spring water in Dongrae hot spring has been changed. In this study, long-trem water level data of Dongrae hot spring were examined for recognizing the change of the hot spring. By the fluctuation analysis of the hot spring water level from January 1992 to July 2018, the maximum and minimum annual drawdowns of no. 27 well were 137.70 and 71.60 meters, respectively, with an average drawdown of 103.39 m. On the other hand, the maximum and minimum annual drawdowns of no. 29 well were 137.80 and 71.70 meters, with an average drawdown of 103.49 m. Besides, drawdown rate became bigger in recent years. As a result of analyzing autocorrelation of the two wells, the correlation coefficient ranged from 0.919 to 0.991, showing seasonal groundwater level fluctuation. The cross correlation analysis between water level and precipitation as well as water level and hot spring discharge resulted in the correlation coefficients of -0.280 ~ 0.256 and 0.428 ~ 0.553, respectively. Therefore, using Dongnae hot-spring water level data from 1992 to 2018, the Mann-Kendall test and Sen's test showed that the continuous decline of water level was mainly caused by the pumping of the hot spring water among various reasons.