• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Journal of Korea Water Resources Association
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• v.30 no.6
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• pp.575-585
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• 1997

A daily runoff system was constructed to support decision making for water use in the downstream region of multipurpose dams in the Han River. The daily runoff system used the modified model from NWSRFS by Tabios III et al. (1986), and potential evapotranspiration was computed from Penman equation. DWOPER was used for channel routing. While the North Han River is the main river reach in the channel routing system, the South Han River and the Soyang River became tributaries. The rainfall-runoff model was calibrated and verified for five subbasins. Daily runoffs were simulated with the hydrometeorological data in 1986 and1990. The simulations were performed from April to November, and the sum of computed discharges for seven or thirty days were compared with actual releases of the downstream dams. It showed the average absolute errors of 8.7 ~31.6%. The sum of total discharges were 10% or less. While stage errors were produced by 0.5 m or less at Yoju station in the ease of simulation from April to August in 1986, the errors kept under 0.2 m since September. In the simulation for 1990, we compared two simulation results. One is produced from real internal and downstream boundary conditions and the other is one from internal and downstream boundary conditions fixed arbitrarily. The two cases showed similar results.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.97-106
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• 2009

The purpose of this study is to analyze factors for resolving problems of Jejusi Residential Parking Permit Program and to draw up a plan by examining Jejusi case. This program was started by way of showing an example in October, 2005, and then has been put in practice in the heart of Jejusi since October, 2007. Jejusi government introduced this system to prevent all kinds of accidents by the indiscreet parking near the residental street and to guarantee the rights to live comfortably by encouraging a pleasant parking environment. As the result of the survey which is about residents' participation from the process of decision-making, the answers such as "Should Participate" and "Surely should participate" are at the high rate of 87.5 percent. A matter of the utmost importance is that this system should be reformed to make the visitors pay parking if they want to park near there. Almost 36 percent of the respondents have a negative opinion, and this is because they consider their visitors. Especially the important factors from the Logistic Regression Analysis are that the government should exercise stricter control over illegal parking, that the system should be improved for the visitors to pay parking, and that the government should support the declining sales of the shops near shopping streets. The suggestions are as follows. First, the government should enforce on reducing the illegal parking. Second, they should secure the parking lots for visitors. Third, they should minimize the impact on the declining sales of the shops near shopping streets.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.189-203
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• 2013

The purpose of this study is to build a GIS database that can utilized to provide a multi-dimensional analysis of aquatic health ecosystem. Especially, it was to build a GIS database for comprehensive analysis using the aquatic ecosystem health. So we collected data on aquatic ecosystem health assessment, Korea Reach File(KRF), Stream Naturalness and Water Environmental Information System, and detailed analysis of the collected data was performed. In addition, the core objects were extracted from individual data and a related entity was derived by pulling out the items associated with thematic characteristics and classifying them. The establishment of GIS database makes it possible to support the decision making for the user to quickly understand the information of water environment. Therefore, the database will provide the information for the effective management on water environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.649-658
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• 2009

The recent emergence of the paradigm of new urban planning for building intelligent urban spaces, such as U-City and U-Eco City, of which the concept of ubiquitous technology is applied, requires high quality three-dimensional spatial information of the urban area. The aim of this study is to build a multi-dimensional spatio-visual information system that includes the solution for visualization, spatial information search, analysis, and evaluation by integrating various types of 3D-modeled spatial information concerning the large urban-size area based on the latest GIS application technology. The range of this study is the integration, visualization, and utilization of spatial information with the goal of building 3D virtual urban environment of high-quality and high-resolution by increasing the utilization of the systematic urban facilities in order to fully reflect the actual user's needs, using the aerial LiDAR data as the plan to overcome the limitations of the existing 3D urban modeling. By reproducing the virtual urban environment the most similar to the actual world through the mash-up of satellite images and aerial photos on the standard format of spatial information constituted of properties and signs, the system will be built with many analysis and utilization functions that support the view and sunlight analysis, various administrative tasks, as well as the decision making process of the city.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.73-78
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• 2019

Recently, there is a need to introduce a Korean-style restriction sandbox system that exempts or suspends existing regulations so that new products or services based on new technologies can be commercialized without restrictions. In response, the government reorganized the relevant statutes to promptly check regulations centering on four fields, including industrial convergence, ICT, FinTech, and regional innovation growth, and to allow experimental, proof and market releases by setting certain conditions(zone, period, scale, etc.). However, despite the same regulatory sandbox application, depending on the nature of the field applied, differences in application subject, whether application of regulatory specifics, system of push ahead decision-making and whether support of financial and taxation are shown. This research is intended to present efficient operation measures for successful settling of Korean-style regulation sandboxes by comparing and analyzing, centering on the Industrial Fusion Promotion Act in the Industrial Convergence Field, ICT field's Information and Communication Convergence Act, FinTech field's Financial Innovation Act and Regional Special Zone Act in the Regional Innovation and Growth Sector.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of the Korean Geographical Society
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• v.50 no.3
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• pp.255-276
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• 2015

This paper presents a multi-agent system model of land-use and cover changes, which is developed and applied to the Gariwang-san and its vicinity, located in Pyeongchang and Jeongseon-gun, Gangwon province, Korea. The Land Use Dynamics Simulator (LUDAS) framework of this study is well suited for representing the spatial heterogeneity and dynamic interactions between human and natural environment, and capturing the impacts of forest-opening policy interventions to future socio-economic and natural environment changes. The model consists of four components: (1) a system of human population, (2) a system of landscape environment, (3) decision-making procedures integrating human(or household), environmental and policy information into forest land-use decisions, and (4) a set of policy scenarios that are related to the forest-opening. The results of model simulation by different combination of various forest management scenarios are assessed by the levels of household income, ecosystem service value and income inequality in the study region. As a result, the optimal scenario of forest-opening policies in the study region is to open the forest to local residential community for the purpose of recreation, considering the distinctive topographical feature. The model developed in this research is expected to contribute to a decision support system for sustainable forest management and various land-use policies in Korea.

• International Commerce and Information Review
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• v.4 no.2
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• pp.253-277
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• 2002

Nowaday, the advanced technology in information and communication has been leading the dramatic change of transaction paradigm expansion from physical basis to electronic one. As we know, financial services support most of financial exchange between two business parties. So the expansion of electronic transaction paradigm affects to every financial institutions which provide financial services. Thus, financial institutions have accepted e-Finance systems and providing internet financial services to live in the competition. The purpose of this study is to contribute the qualitative enhancement of its customer service, rapid diffusion and accurate strategy establishment for e-Finance industry in the user side. Through the literature review and factor and reliability analysis, this study selects six diffusion factors such as efficiency of perceived e-Finance, reliability and safety of e-Finance in perceived e-Finance itself's characteristic; confidence, technical factors and the customer service quality of e-Finance system in perception on e-Finance System; inclination to innovation in the personal characteristic. According to result of hypothesis verification by using logistics regression analysis, technical factors and the customer service quality of e-Finance system in perception on e-Finance System and inclination to innovation in the personal characteristic gave statistically positive effect to the diffusion decision at the significant level 0.05 and 0.01. However efficiency of perceived e-Finance, reliability and safety of e-Finance in perceived e-Finance itself's characteristic didn't affect to diffusion decision and confidence of e-Finance system in perception on e-Finance System didn't have any statistical significancy. This study can be used as a basic material for the forward empirical study of diffusion factors in the user side and be able to apply to company and government policy making or embodiment, determination for customer service quality degree of financial institutions. But this study has some limitations like didn't touch satisfaction factors and its effect, only deal domestic customers and didn't use multi-regression analysis.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1061-1061
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• 2001

The scope of precision agriculture is to reach the put up cultivation goals by adjusting inputs as precise as possible after what is required by the soil and crop potentials, on a high spatial resolution. Consequently, precision agriculture is also often called site specific agriculture. Regulation of field inputs “on the run” has been made possible by the GPS (Geographical Position System)-technology, which gives the farmer his exact real time positioning in the field. The general goal with precision agriculture is to apply inputs where they best fill their purpose. Thus, resources could be saved, and nutrient losses as well as the impact on the environment could be minimized without lowering total yields or putting product quality at risk. As already indicated the technology exists to regulate the input based on beforehand decisions. However, the real challenge is to provide a reliable basis for decision-making. To support high spatial resolution, extensive sampling and analysis is required for many soil and plant characteristics. The potential of the NIR-technology to provide rapid, low cost analyses with a minimum of sample preparation for a multitude of characteristics therefore constitutes a far to irresistible opportunity to be un-scrutinized. In our work we have concentrated on soil-analysis. The instrument we have used is a Bran Lubbe InfraAlyzer 500 (1300-2500 nm). Clay- and organic matter-contents are soil constituents with major implications for most properties and processes in the soil system. For these constituents we had a 3000-sample material provided. High performance models for the agricultural areas in Sweden have been constructed for clay-content, but a rather large reference material is required, probably due to the large variability of Swedish soils. By subdividing Sweden into six areas the total performance was improved. Unfortunately organic matter was not as easy to get at. Reliable models for larger areas could not be constructed. However, through keeping the mineral fraction of the soil at minimal variation good performance could be achieved locally. The influence of a highly variable mineral fraction is probably one of the reasons for the contradictory results found in the literature regarding organic matter content. Tentative studies have also been performed to elucidate the potential performance in contexts with direct operational implications: lime requirement and prediction of plant uptake of soil nitrogen. In both cases there is no definite reference method, but there are numerous indirect, or indicator, methods suggested. In our study, field experiments where used as references and NIR was compared with methods normally used in Sweden. The NIR-models performed equally or slightly better as the standard methods in both situations. However, whether this is good enough is open for evaluation.