Earticle

본 논문은 내항상선 선원의 수급 안정화를 기하여 연안해운의 발전을 도모하기 위하여 구체적으로 내항상선 선원의 수급실태의 분석을 통해 향후 내항상선 선원의 수요 전망을 예측하고자 하는 것이다. 연안 해운기업의 경쟁력 강화에 있어서 선원수급과 선원인력양성의 필요성을 인지하고, 특히 인력수요예측의 정밀성을 높이고 지속적이고 피드백이 가능한 예측 프로세스를 모색하는 것은 현재 연안해운기업의 열악한 선원인력관리의 어려움을 극복하기 위한 단초로서 현재 시의적절한 연구주제가 될 것이다. 향후 내항상선 선원의 수요부문에서 선박 척수의 변화에 따른 시뮬레이션 결과, 증가율 기준을 0.1%~1% 폭의 수준을 상정할 경우 7,879~8,258명으로 예측되었다. 이는 2009년 현재 7,831명 수준에서 매년 약 20~430명의 추가 인력이 투입되어야 함을 의미한다. 일반적으로 5년 내지 10년 단위로 단속적으로 예측치를 제시하는 방법은 예측의 사후추적이 부실한 관계로 예측정확도가 떨어지기 쉬운 점을 선행연구 검토 부분에서 확인하였으며, 본 연구와 같이 현황자료를 기초로 예측치와 실제치의 차이에 대한 피드백을 위해 매년 평가를 실행하고 그 결과를 차기년도 예측에 반영하는 접근방법을 도입한다면, 선원인력의 수급에 대한 예측정확도를 높일 수 있을 것이다.

This study focused on the supply-demand and training system of the crew for domestic coastal shipping. First of all, it forecasted the prospect and effect in the future of the crew supply-demand through the analysis to the current situation of crew employment and the internal and external environment changes. Next, it suggested the specific role and alternatives of government, industry and educational institutions after the comparison and examination of the sailor policies among Korea and major shipping countries. In regard to the demand of crew manpower in coastal shipping, it figured out the bottoms and the current circumstances of sailors, and it could anticipate the future demand by the gradational approach. According to the findings, firstly the result of this simulation by the changes of the ship numbers demonstrated that the demand over the next 10 years will be 7,890~8,025 in the case of the growth 0.4%, and 7,894~8,063 in 0.5%. Secondly, assuming the growth 0.1~1%, the result illustrated that the demand will come to 7,879~8,258. This means the fact that the additional manpower has to be input to 20~430 annually from now on. To conclude, this study showed the more rational numbers about the supply-demand than the past researches and displayed the systematic approach to supply and train the crew in domestic coastal shipping.

Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment has been active on transport infrastructure. But investment of transport infrastructure has more risks than others due to overforecast of transport demand for ensuring project validity, and cost uncertainty arising from financial crisis, commodity prices and so on. In the case of Incheon international airport express, after 2 years and 6 months, Incheon international airport express is opened, Korail take over equity stake in private investor due to the problems of MRG(Minimum Revenue Guarantee) be contracted with private investor. Not only that, in other case of Yong-in light rail, it is ongoing for legal disputes between Yong-in local government and private investor on account of opening delaying. On current Investment Assessment System of Transport Infrastructure, Risk Management system on investment of transport infrastructure is inadequate because Sensitivity Analysis in economic efficiency have been performed on the simple method which only changes benefits, expense and social discount rate. For this reason, this study analyze risks for investment of transport infrastructure demand forecast, and rise to the management practice for every particular item.

High level of accuracy in forecasting heat demand of each district is required for operating and managing the district heating efficiently. Heat demand has a close connection with the demands of the previous days and the temperature, general demand forecasting methods may be used forecast. However, there are some exceptional situations to apply general methods such as the exceptional low demand in weekends or vacation period. We introduce a new method to forecast the heat demand to overcome these situations, using the linearities between the demand and some other factors. Our method uses the temperature and the past 7 days' demands as the factors which determine the future demand. The model consists of daily and hourly models which are multiple linear regression models. Appling these two models to historical data, we confirmed that our method can forecast the heat demand correctly with reasonable errors.

본 연구의 목적은 평양 및 백두산 관광 등 남북한의 교류에서 발생하는 항공여객과 항공물동량 수요를 예측함으로써 향후 남북한간 교류협력 활성화시 원활한 항공교통서비스를 제공할 수 있도록 하는 데 있다. 본 연구에서는 남북한간 교류협력 시나리오의 전개에 따라 항공수요가 획기적으로 도약할 수 있는 상황을 상정하고, 기술적으로는 회귀분석의 툴을 적용하였다. 회귀분석을 통해 전체 교류인원을 예측한 후 전체 교류인원에 대한 항공교통의 비중을 적용하여 항공여객 수요를 예측하였다. 또한, 예측된 항공여객 수요로부터 추정한 항공물동량을 포함하여 공항 및 노선별 항공편을 예측하였다.

This paper aims to predict air passenger and air freight demands in the air routes between South and North Korea. The air demands will be fostered by the visitors of Pyeongyang and Baekdu Mountain, whose forecasts will be used for supplying the air traffic services necessary for the active exchange and cooperation between South and North Korea in the future. The authors use the tool of regression analysis under the assumption of epoch-making progress in demand for aviation in accordance with the exchange and cooperation scenario between South and North Korea. After predicting the total number of travelers through regression analysis, the authors applied the share of air passengers among total travelers in order to predict the number of air passengers. Finally, the number of flights of each airport and route were forecasted by including the air freight, estimated from the number of air passengers.

In general, short term load forecasting is based on the periodical load pattern during a day or a week. Therefore, the conventional methods do not expose stable performance to every day during a year. Especially for anomalous weather conditions such as typhoons, the methods have a tendency to show the conspicuous accuracy deterioration. Furthermore, the tendency raises the reliability and stability problems of the conventional load forecast. In this study, a new load forecasting method is proposed in order to increase the accuracy of the forecast result in case of anomalous weather conditions such as typhoons. For irregular weather conditions, the sensitivity between temperature and daily load is used to improve the accuracy of the load forecast. The proposed method was tested with the actual load profiles during 14 years, which shows that the suggested scheme considerably improves the accuracy of the load forecast results.

정보보호시스템 평가수요의 예측은 예측된 평가수요를 근거로 적극적인 평가서비스를 제공하기 위하여 필요하다. 평가수요예측을 하기위하여 일반적으로 설문조사를 이용하지만 무응답 및 불성실한 응답으로 인하여 설문응답 자료만으로 평가수요를 예측하기에는 부족하다. 따라서 설문조사의 평가수요를 보정할 수 있는 모형이 필요하다. 본 논문에서는 설문조사를 통하여 예측 할 수 있는 직접적인 평가수요와 통계적 모형을 이용한 간접적 평가수요를 비교하고 설문조사의 대체 방법을 제시하였다.

국내 이동통신 서비스 시장은 급속하게 발전해왔다. 이러한 성장에 맞춰 WCDMA 서비스가 중요한 성장 동력으로 기대했으나 해외에 비해 국내 보급률은 더딘 실정이다. 하지만 HSDPA의 상용화가 이루어지면서 정체된 WCDMA 단말기의 수요를 이끌 것으로 예상된다. 따라서 신규 WCDMA 서비스의 수요를 예측하고 그에 맞는 새로운 이동통신 사업 전략을 세우는 것이 필요할 것이다. 본 논문은 이동통신 단말기의 가격과 성능에 따른 소비자의 구매 효과를 반영하고, 변형된 Lotka-Volterra 예측 모형을 개발하여 향후 WCDMA 서비스 가입자를 예측하였다.

The demand of domestic mobile service has been explosively increasing. The forthcoming WCDMA, which open in 2006, is also a key technology in the mobile service market. The WCDMA service needs HSPDA phones which will be evolved to HSDPA. In the aspect of drawing up management strategy, practical researches about forecasting the demands of new mobile phones are necessary. In this paper, we provide the modified the Lotka-volterra model as a forecasting model, which is concerned with effects of phone prices and performance.

오늘날 기업들이 급격한 환경변화에 능동적으로 대처하고 지속적인 기업의 성장과 발전을 이루기 위해서는 물류유통과 수요예측에 대한 전반적인 이해와 이를 바탕으로 한 전반적인 시스템이 구축되어야한다. 기업의 성장을 위하여 지속적인 물류유통과 수요예측과 결정이 있어야 한다. 또한 이에 대한 공통적인 적용사항을 규칙 기반으로 한 시스템인 설계되어야한다. 그래서 본 논문에서는 규칙을 기반으로 기업의 물류유통/수요예측을 위하여 데이터마이닝 기법을 적용한 검색 기법을 제시하고자 한다.

An effective methodology is reported for determining the optimal lot size of batch processing and storage networks which include uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, infernally consumed, transported to or from other sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sires while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of the global supply chain.

An areal elderly migration model (AEMM) was developed to assess the demand of rural development projects targeted towards elderly people. The AEMM was developed with adaptation of the gravity model to represent spatial interaction regarding amenities. Areal characteristics were classified for estimating the amenities from the perspective of net migration. From 1990 to 2000, data were acquired from USCB, PASDA, PAHEALTH, PADCNR, PFBC, and NCDC in 67 Pennsylvania counties for analysis and application. The results revealed that elderly migration can be explained not only by areal characteristics but also by spatial interaction considering the population, distances, and amenities of surrounding areas.

High accuracy of the load forecasting for power systems improves the security of the power system and generation cost. However, the forecasting problem is difficult to handle due to the nonlinear and the random-like behavior of system loads as well as weather conditions and variation of economical environments. So far. many studies on the problem have been made to improve the prediction accuracy using deterministic, stochastic, knowledge based and artificial neural net(ANN) method. In the conventional load forecasting method, the load forecasting maximum error occurred for the holidays on Saturday and Monday. In order to reduce the load forecasting error of the daily peak load for the holidays on Saturday and Monday, fuzzy concept and linear regression theory have been adopted into the load forecasting problem. The proposed algorithm shows its good accuracy that the average percentage errors are 2.11% in 1996 and 2.84% in 1997.

본 논문에서는 철도 수요예측 문제의 유형을 목적에 따라 3가지로 분류하였고, 최근 철도자원을 재고관리 차원에서 접근하고자 하는 시각에 따라 분배모형으로써 적응필터를 사용하는 방법의 타당성에 대해 설명하였다. 또 철도 승객수요의 주요 특징을 분석하였으며, 철도 승객수요 예측의 요구사항 및 방법론을 대규모 재고관리 시스템의 일반적 요구사항에 따라 정리하였다. 영향인자에 대한 분석으로 요일별 계절변동 지수를 정량적으로 산정하였다. 적응필터를 이용한 철도 승객수요 예측의 예제를 제시하였으며, 예측에의 정확성에 대한 비교를 제시하였다.