• Knowledge Management Research
• /
• v.22 no.4
• /
• pp.71-85
• /
• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Korean Journal of Remote Sensing
• /
• v.30 no.1
• /
• pp.61-73
• /
• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• Korean Chemical Engineering Research
• /
• v.52 no.5
• /
• pp.564-573
• /
• 2014

Economic optimization of cumene manufacturing process to produce cumene from benzene and propylene was studied. The chosen objective function was the operational profit per year that subtracted capital cost, utility cost, and reactants cost from product revenue and other benefit. The number of design variables of the optimization are 6. Matlab connected to and controlled Unisim Design to calculate operational profit with the given design variables. As the first step of the optimization, design variable points was sampled and operational profit was calculated by using Unisim Design. By using the sampled data, the estimation model to calculate the operational profit was constructed, and the optimization was performed on the estimation model. This study compared second order polynomial and support vector regression as the estimation method. As the sampling method, central composite design was compared with Hammersley sequence sampling. The optimization results showed that support vector regression and Hammersley sequence sampling were superior than second order polynomial and central composite design, respectively. The optimized operational profit was 17.96 MM$ per year, which was 12% higher than 16.04 MM$ of base case.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.1
• /
• pp.53-62
• /
• 2015

The water vapor including latent heat is the important component in an atmospheric circulation and in a monitoring of the Earth's climate changes, as well as in the weather forecast improvement. In this study, to establish the Algerian weighted mean temperature model, a linear regression method had been developed under 5 radiosonde observations for a total 24,694 profiles from 2004 to 2013. An weighted mean temperature is a key parameter in the processing of PWV from GNSS tropospheric delays. The result from the study has expected to provide an useful model to demonstrate the realization and utility of using the ground-based GNSS meteorology technique that will bring improvements in weather forecasting, climate monitoring in Algeria.

• Journal of the Institute of Convergence Signal Processing
• /
• v.1 no.1
• /
• pp.15-22
• /
• 2000

The analysis of power spectrum based on linear AR model is applied widely to quantize the response of autonomic nerve noninvasively, In this paper, we estimate the power spectrum density for heartrate variability of the electrocadiogram and pulse wave for short term data(less than two minute), The time series of heart rate variability is obtained from the time interval(RRI, PPI) between the feature point of the electrocadiogram and pulse wave for normal person, The generated time series reconstructed into new time series through polynomial interpolation to apply to the AR mode. The power spectrum density for AR model is calculated by Burg algorithm, After applying AR model, the power spectrum density for heart rate variability of the electrocadiogram and the pulse wave is shown smooth spectrum power at the region of low frequence and high frequence, and that the power spectrum density of electrocadiogram and pulse wave has similar form for same subject.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.10 no.6
• /
• pp.81-87
• /
• 2010

In order to calculate the accurate runoff from a basin, nonlinearity in the relationship between rainfall and runoff has to be considered. Many runoff calculation models assume the linearity in the relationship or are too complicated to be analyzed. Therefore, the storage function method has been used in the prediction of flood because of the simplicity of the model. The storage function method has five parameters with related to the basin and rainfall characteristics which can be estimated by the empirical trial and error method. To optimize these parameters, regression method or optimization techniques such as genetic algorithm have been used, however, it is not easy to optimize them because of the complexity of the method. In this study, the metamodel is proposed to estimate those model parameters. The metamodel is the combination of artificial neural network and genetic algorithm. The model is consisted of two stages. In the first stage, an artificial neural network is constructed using the given rainfall-runoff relationship. In the second stage, the parameters of the storage function method are estimated using genetic algorithm and the trained artificial neural network. The proposed metamodel is applied in the Peong Chang River basin and the results are presented.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.1
• /
• pp.289-295
• /
• 2024

This study analyzes the correlation between the accracy of rifle and the result of engagement. And estimates the improvement cost of the rifle accordingly. For this experiment, an engagement class simulation model(AWAM: Army Weapon Effectiveness Analysis Model) was used. We also selected the rifle, which is a portable weapon for the experiment. Prior to this experiment, we conducted a reliability test(VV&A: Verification, Validation and Accreditation) on the model. The VV&A process is mainly done during the development of the DM&S model, which is also necessary for the operation of the M&S. We confirmed the need for VV&A during the experiment and obtained reliable experimental results using the corrected values. In the Accuracy Experiment we found that the 20% improvement is the most effective. And we were able to estimate the cost of acquiring a rifle with a 20% higher accuracy. The cost was estimated by simple regression analysis based on the price of the current rifle. Through this study, we could know the impact of the accuracy of rifle on the experimental results and estimate the cost of improved rifle.

• Journal of Korean Society of Forest Science
• /
• v.86 no.3
• /
• pp.365-377
• /
• 1997

Much of the Cumberland Plateau of Tennessee, USA is in mixed hardwoods for which there are no applicable growth and yield predictors. Use of site index as a variable in growth and yield prediction models is limited in most stands because their history is not known and many may not be even-aged. Landtypes may offer an alternative to site index for these mixed stands because they were designed to include land of about equal productivity. To determine vegetation by landtype, dependency between landtype and detailed forest type was tested with Chi-square. Differences in productivity among landtypes were tested by employing regression analyses and analysis of variance(ANOVA). Basal area growth was fitted to the nonlinear models developed by Moser and Hall(1969). Basal area growth and volume growth were also predicted as a function of initial total basal area and initial volume with linear regression by landtype and by landtype class. Differences in basal area growth and volume growth by landtype were tested with ANOVA. Dependency between site class and landtype was tested with Chi-square. Vegetation types seem to be related to landtypes in the study area although the validity of the test is questionable because of a high proportion of sparsely occupied cells. No statistically significant differences in productivity among landtypes were found in this study.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.707-725
• /
• 2021

Energy management systems (EnMS) contribute to sustainable energy saving and greenhouse gas reduction by emphasizing the role of energy management in production-oriented economies. Although understanding the methods used to measure energy performance is a key factor in constructing successful EnMS, few attempts have been made to examine these methods, their applicability, and their utility in practice. To fill this research gap, this study aimed to deepen the understanding of energy performance measures by focusing on four energy performance indicators (EnPIs) proposed by ISO 50006, namely the measured energy value, ratio between measured values, linear regression model, and nonlinear regression model. This paper presents policy and managerial implications to facilitate the effective use of these measures. An analytic hierarchy process (AHP) analysis was conducted with 41 experts to analyze the preference for EnPIs and their key selection criteria by the industry sector, and organization and user type. The findings suggest that the most preferred EnPI is the ratio between the measured values followed by the measured energy value. The ease of use was considered to be most important while choosing EnPIs.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.33 no.4
• /
• pp.148-159
• /
• 2021

This study estimates the region of freshwater influence (ROFI) by Han River discharge in the Yeomha channel, Gyeonggi Bay. A 3-D numerical model, which is validated for reproducibility of variation in current velocity and salinity, is applied in Gyeonggi Bay. Distance of freshwater influence (DOFI) is defined as the distance from the entrance of Yeomha channel to the point where surface salinity is 28 psu. Model scenarios were constructed by dividing the Han River discharge into 10 categories (200~10,000 m³/s). The relation equation between freshwater discharge and DOFI was calculated based on performing a non-linear regression analysis. ROFI in Yeomha channel expands from the southern sea area of Ganghwa-do to the northern sea area of Yeongheung-do as the intensity of Han River discharge increases. The discharge and DOFI are a proportional relationship, and the increase rate of DOFI gradually decreases as discharge increases. Based on the relation equation calculated in this study, DOFI in the Yeomha channel can be estimated through the monthly mean Han River discharge. Accordingly, it will be possible to respond and predict problems related to damage to water quality and ecology due to rapid freshwater runoff.