• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.3 s.59
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• pp.63-73
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• 2006

Auctions have been traditionally used to find the current price of goods when little is known about their true value. A special auction methodology, called a 'simultaneous multiple round auction', is available to auction radiofrequency spectrum where all lots are simultaneously on of for over multiple rounds of bidding. This type of auction is especially useful when there are lots that are of essentially equal value and substitutable, except that different bidders may prefer different combinations of lots. By using multiple rounds, a bidder has the opportunity to gather information concerning the value of individual lots and can change strategy by shifting the bidding to another preferred combination if one combination becomes too expensive. Information is released in three main ways during an auction: Bidder Status; High Bids; and Bandwidth Value.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.126-128
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• 2006

현재 배전부분도 사업부체제로 진행됨에 따라 구역 및 지역별로 배전계통을 운영하는 경쟁체제에 돌입하게 되었다. 또한 각 사업부별로 예산을 추진하여 배전계통을 운영하게 되며 배분된 예산으로 배전계통의 신뢰도 및 경제적 운영을 일정 수준으로 유지하여 타 사업부와 사업성을 경쟁해야 한다. 특히, 각 배전 사업부별로 경쟁해야 하므로 최소의 비용으로 최대의 유지보수 효과를 얻을 수 있는 방법을 개발해야 하며, 비용을 최소로 하여 최적의 점검 주기를 찾는 문제는 중요하다고 할 수 있다. 본 논문에서는 최적 유지보수 기기 선정과 최적 유지보수 주기를 결정하는데 있어서 적합한 기법인 배전 계통 유지보수 기법(Reliability Centered Maintenance, RCM)을 이용하였다. 이의 구현을 위하여 Markov chain 기법을 배전 계통 기기의 유지보수 모델에 적합하도록 수정하여 유지보수에 필요한 비용과 기기의 고장으로 인하여 발생할 수 있는 정전비용 등을 고려하여 최적의 점검 주기를 결정하고자 한다. 제안된 RCM의 알고리즘은 Dynamic Programming을 이용하여 점검 및 유지보수에 필요한 기기를 결정하는 부분과 유지보수의 실행 여부를 결정하는 decision 부분으로 되어있다. 사례연구를 통하여 본 논문에서 제안된 알고리즘의 적용가능성을 살펴보았다.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1361-1364
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• 2009

최근 몇 년동안 지속가능하고 효과적인 수자원 관리는 전체적인 접근방법이 요구되고 있으며, 사회와 경제발전과 생태계 보호 및 토지이용과 수자원 이용의 적절한 관리와 연결된 개념이 필요하다. 이러한 관점에서 유역을 간단한 고정된 지역적인 문제라고 생각하는 것보다 전체로서의 유역 기능을 개선하는데 노력이 필요하다. 또한 사회와 경제발전으로 인해 도시화, 여가 관광지역 및 사회기반시설의 확장 그리고 자연환경의 변화가 발행하고 있다. 효과적인 토지이용 배분과 자연지역의 보호도 중요하지만 잠재적인 홍수피해 저감도 중요한 문제이다. 토지이용의 변화는 많은 이해관계자들로부터 유발되는 문제이기 때문에 거시적인 관점에서 고려되어야 한다. 본 논문은 다양한 관계자와 자연환경과의 연결과 상호작용 유형을 이해하고 다양한 정책선택과 자연환경 상태가 토지이용 변화에 미치는 영향을 이해하고자 한다. 인간의 활동으로 인해 발생하는 토지이용의 변화를 모의하기 위해서 행위자기반모형(Agent based Model, ABM)으로 접근하고자 한다. ABM은 유역관리의 이해당사자간의 정책과정을 도출하고 다양한 유역관리 대안을 평가하기 위해서 홍수위험, 자연개발 및 비용과 같은 유역관리의 영향을 설명하는 통합된 유역모델이다. 여기서 토지이용은 경제적, 지형학적 상황, 공간계획 및 홍수방어정책에 좌우되며, 토지의 속성과 규칙을 통해 토지이용이 선택되게 된다. 본 모형을 통해 공간적으로 분포된 행위자의 운영을 기반으로 종합적인 토지이용 패턴을 분석하였다, 이를 통해 토지이용 결정에 영향을 주는 인자를 추정하여 통합홍수관리 목적에 맞는 관리 대책의 결정 및 설계를 가능토록 하였다.

• Journal of the KSME
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• v.25 no.4
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• pp.266-273
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• 1985

자동차공업의 미래를 점치는 전문가들은 1980 후반에서 1990년대에 제 4세대의 자동차공업의 핵심은 한국, 멕시코, 브라질을 중심으로 한 저생산요소 요인이 있는 국가에서 생산이 중점적으로 된다는 전망과 유동제조시스템(FMS)을 활용한 지역적으로 안분된 생산체제로 새로운 형태의 경쟁협력 관계가 발생하리라는 예측이 엇갈린다. 유동제조시스템에서 주요역할을 하는 부분은 생산순서를 결정하는 이론인데 현재의 저산기의 논리는 인간의 두뇌에 비교하면 아직 매우 단 순하고 원시적인 편이다. 현재 많은 노력이 경주되는 인공두뇌(artifical intellegence: Al)에 관한 연구에 많은 진전이 있다고 하더라도 당분간은 인간의 두뇌가 기계의 지능보다 월등한 부문이 있는 반면 인간이 활동하기 불편한 작업환경이 있다든가 단순 작업이 되어 인간에 지루함을 주는 일들이 있어 인간과 기계의 적절한 배분으로 적극 기계를 이용하는 자동화도 필요하지만 동시에 인간의 창의적인 능력을 활용하는 것도 매우 필요하다. 우리나라에서 자동차공업이 국제적으로 발전한다면 이는 한국적인 여건에 부합하는 창의적인 인간활동에 의한 것이지 값싼 노임 때문 만은 아닐 것이다.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.79-84
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• 2014

Increasing demand for realistic media and improvement of transmission and device techniques accelerate ultra-high definition(UHD) service realization. In Korea, the cable TV broadcasting companies are planning to commercialize in Apr. 2014. For the terrestrial TV broadcasting service, technical issues are considered for the specification of UHD broadcasting system. However, the frequency bands and the system bandwidth for the terrestrial UHD broadcasting system have not been decided. In this paper, we propose required spectrum bandwidth for the next-generation terrestrial broadcasting service considering source coding, error correcting codes and modulation techniques. Also, we propose frequency management plan for terrestrial UHD broadcasting system in which we divide all parts of the country into 9 frequency zones and allocate 4 frequency band to each frequency zone considering single frequency network (SFN).

• Journal of the Korean Regional Science Association
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• v.34 no.1
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• pp.19-30
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• 2018

Social overhead capital(SOC) is an essential element for society to be developed and operated normally. In spite of the increase in the importance of SOC, It is difficult to present the criteria for the appropriate investment of SOC. and The discussion on making SOC investments of local government is insufficient. If the local autonomy has been guaranteed, local government increases investment in regional public goods that residents prefer. Reflection of such residents preferences is the driving force to bring the efficiency of resource allocation in the decentralization theorem. In this study, the authority and autonomy of local governments are measured through local finance. and the decision-making of local governments for SOC investment is examined in point of decentralization theorem. In the empirical analysis, the elasticities of fiscal resources are estimated for facilities(road, water and sewage, irrigation canal and flood control) that local governments are involved in investment. These decisions made by metropolitan cities and provinces were different. The difference was most evident in the effect of per capita local tax on investment. These results show that metropolitan cities and provinces that have different situation made investment decisions differently. It shows that local governments reflect the preferences of the residents in making an investment. The main implication of this study is as follow. In case the role of local government in social overhead capital investment is increased, the increase in efficiency of resource allocation occurs. and The fiscal resources must be raised by local taxes rather than the financial resources from the central government.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.05a
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• pp.59-63
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• 2000

At military bases, environmental restoration activities resulting from oil contamination are growing concerns of preventing adverse effects on human health and environments. Its technologies are still under developing stage through some countries such as United States and Germany. This study is focused on developing model for a decision-maker to assist the restoration priority under the situation of limited resources such as budget and time. The Model, named the Base Restoration Priority Decision model(BRP model), is composed of the three factors : oil contaminants receptors, and the potential migration pathways. Each risk rating of factor is combined in the 27 matrix blocks and set immediate, moderate, and delayed action category designated restoration priority. This is categorized to group sites into three degree using the simplest of assessment system. As a result, the model will be able to apply to the effective allocation of resources for the restoration by any decision-maker because the model is easy to understand. Also, the continuous study will have established risk assessment system for the restoration of contaminated military with this study as the starting point.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.339-350
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• 2024

Purpose: This study analyzes accessibility of 10 hydrogen charging stations in Seoul and identifies areas that were difficult to access. The purpose is to re-analyze accessibility by adding a new location in terms of equity and safety of location placement, and then draw implications by comparing the improvement effects. Method: By applying the location-allocation model and the service area model based on network analysis of the ArcGIS program, areas with weak access were identified. The location selection method applied the 'Minimize Facilities' method in consideration of the need for rapid arrival to insufficient hydrogen charging stations. The limit distance for arrival within a specific time was analyzed by applying the average vehicle traffic speed(23.1km/h, Seoul Open Data Square) in 2022 to three categories: 3,850m(10minutes), 5,775m(15minutes), 7,700m(20minutes). In order to minimize conflicts over the installation of hydrogen charging stations, special standards of the Ministry of Trade, Industry and Energy applied to derive candidate sites for additional installation of hydrogen charging stations among existing gas stations and LPG/CNG charging stations. Result: As a result of the analysis, it was confirmed that accessibility was significantly improved by installing 5 new hydrogen charging stations at relatively safe gas stations and LPG/CNG charging stations in areas where access to the existing 10 hydrogen charging stations is weak within 20 minutes. Nevertheless, it was found that there are still areas where access remains difficult. Conclusion: The location allocation model is used to identify areas where access to hydrogen charging stations is difficult and prioritize installation, decision-making to select locations for hydrogen charging stations based on scientific evidence can be supported.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.588-592
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• 2012

저수지에서 퇴사가 저수지에 미치는 영향으로는 저수용량의 감소로 인한 용수공급량 저하, 상류하천 수위 상승에 따른 홍수소통능력 감소로 인한 배수위 상승, 퇴적토의 용출에 의한 부영양화 촉진 및 중금속 퇴적 등의 수질변화, 퇴사로 인한 어류서식처 환경의 변화 등이 있다. 또한, 저수지로 유입되는 유사에 대한 정확한 예측은 댐의 계획 및 운영과 관련된 저수지 퇴사관계를 이해하는데 필수 요소이다. 즉, 저수지 퇴사에 관한 예측 자료는 댐 설계시에 장래 50년 및 100년 후의 저수위-저수용량 관계곡선을 결정하고, 댐의 사수위를 결정하는데 중요한 기본자료이며, 또한 댐 건설후의 저수지내로 유입되는 유사의 공간적 퇴적분포를 예측하고, 기능별 저수지 용량배분, 본체 및 취수구 등 각종 수리구조물의 안정, 저수지 상류 퇴사로 인한 홍수위의 상승 등 저수지 제 기능의 적정 관리를 계획하는데 필요한 기본자료이기 때문이다. 본 연구에서는 저수지 내에서의 2차원적 하상변동을 해석하기 위한 퇴사 모델링 방법으로 2차원 정상 및 동수역학적인 유사이송과 하상변동을 모의할 수 있으며, 침식과 포착 및 이송 그리고 퇴적의 각 단계에 따라 세부모의가 가능할 뿐만 아니라 RMA2와 SMS 프로그램과 상호 연계가 자유로운 SED-2D 모형을 이용하여 댐 축조로 인한 저수지내의 퇴사거동을 모의한 후 하상변동을 분석하였다.