• Proceedings of the Korea Technology Innovation Society Conference
• /
• 2001.11a
• /
• pp.37-57
• /
• 2001

Digital technology enhanced the improvement of technological aspects in the both broadcasting and telecommunications industries. The infrastructures of each industry converged to one, which impacts not only on technology but also on the broadcasting service. The current broadcasting service is characterized by one-way service, but it'll changed to be customized, or two-way service that reflects the interest of customers. This change requires a new standard to categorize and analyze the future broadcasting service converged and market structure, differing from the present standard based on the transmission channels. This study aims at forecasting the demand of interactive TV service as a representative broadcasting service in the near future, and analyzing the market structure of the broadcasting services. We assume that the present broadcasting and information and telecommunications services such as terrestrial, cable TV, satellite, digital TV services and high-speed broadband service have strong relationship with interactive TV service. First we use Bass diffusion method to predict the diffusion curve of the present five services. Then we analyze the relationship between the present services and interactive TV service by Delphi method. Finally we estimate the potential subscription number of interactive TV service based on the relationship among the services and diffusion parameters.

• KIEAE Journal
• /
• v.9 no.4
• /
• pp.29-36
• /
• 2009

Artificial ground greening has been developed gradually in accordance with increasing demands of out-door space in Apartment complexes. Nowadays other social demand, environmental load abatement, needs qualitative growth of artificial ground greening as well as quantitative growth. So the objects of this study would be seizing and analyzing changeable items in artificial ground greening in the future, and show drafting materials for the development of spheres in connected with artificial ground greening. For this study, Delphi method was applied. First, three groups of panel, 48 people, were selected. Second, set up items of changes possible in the future from the first questionnaire and additional inquiry. Third, made up the second questionnaire of change possible in the future with Likert summated scale, and finally one way - ANOVA executed; independent variables were items of changes, and dependent variables were three groups of panel. To conclude, although limits of this study, we could glance over general flows and changes in artificial ground greening, and discover items which are hardly changeable and necessary to change in present condition of artificial ground greening.

• KIEE International Transactions on Power Engineering
• /
• v.5A no.4
• /
• pp.331-338
• /
• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• Water Engineering Research
• /
• v.5 no.3
• /
• pp.111-121
• /
• 2004

For the long-term strategic water resources planning, forecasting the future streamflow change is important to meet the demand of a growing society. The streamflow variation to the decade-long precipitation was investigated for the two major stage gauging stations in Korea. Precipitation and runoff characteristics have been analyzed at Yongwol stream stage in the Han River as well as Sutong stream stage in the Kum River for the future water resources management strategies. Monte Carlo method has been applied to estimate the future precipitation and runoff. Based on the trend line of 10-year moving average of runoff depth for the historical runoff records, the relation between runoff and the time variation was examined in more detail using regression analysis. This study showed that the surface flows have been significantly decreased while precipitation has been stable in these basins. Decreasing in runoff reflects the regional watershed characteristics such as forest cover changes. The findings of this study could contribute to the planning and development for the efficient water resources utilization.

• The Journal of Information Systems
• /
• v.29 no.3
• /
• pp.119-144
• /
• 2020

Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

• Proceedings of the KIEE Conference
• /
• summer
• /
• pp.695-697
• /
• 2004

현재 전력시장에서 발생하는 게이밍을 반영하기 위한 수리적 모델로서 가장 보편적으로 사용되는 이론 중의 하나가 쿠르노 모델이다. 쿠르노 모델을 실제전력시장에 적용할 때 가장 어려운 점 중의 하나는 정화한 해당 모델에 사용되는 수요와 시장가격간의 관계를 정식화한 수요반웅함수(혹은 역수요함수)를 구하는 것이 다. 기존 모델의 경우 장기간에 걸친 탐문조사나 데이터를 바탕으로 가격탄력성을 구하는 방식을 취하고 있다. 그러나 수요는 전기설비의 교체 소비자의 기호 등 여러가지 변수로 지속적으로 변할 수 있기 때문에 이러한 고정적인 가격탄력성을 적용하는 것은 문제점이 될 수 있기 때문에 본 논문에서는 이러한 가격탄력성을 일정 거래주기 마다 갱신해줄 수 있는 방법을 제안하고자 한다.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.51 no.12
• /
• pp.597-602
• /
• 2002

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model have been studied, proposed, and applied. Among those models, power pool is more popular than other. This paper assumes the power pool market structure having competitive generation sector, and a new method is presented to build a bidding strategy in that market. The utilities participating in the market have the perfect information of their cost and price functions, but they don't know which strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's strategy using Nash equilibrium or stochastic methods. And he also has to forecast the system demand. According to this forecasting result, his payoffs can be changed. Considering these all conditions, we formulate a bidding game problem and apply noncooperative game theory to that problem for the optimal strategy or solution. Some restrictive assumption are added for simplification of solving process. A numerical example is given in Case Study to show essential features and concrete results of this approach.

• Current Industrial and Technological Trends in Aerospace
• /
• v.8 no.1
• /
• pp.12-22
• /
• 2010

The great recession which caused by financial crisis made steep rise of oil price and the serious problems of the aircraft industry. High oil price increases operating cost and the recession decreases air traffic. After a period of high book order and delivery from global economic recovery, the aircraft order fell down suddenly. Also the Aircraft price and lease rate deceased and the MRO market is reduced, too. But, the air cargo and passenger increase again since late of 2009. So, it is difficult to predict the market movement, most of the forecasters agreed that the air traffic and aircraft demand will grow gradually in long term with the growth of emerging markets like China, India and Africa. And more efficient, safe and clean aircraft is needed and will need in the market.

• Proceedings of the KSR Conference
• /
• 2010.06a
• /
• pp.1615-1622
• /
• 2010

Recently, there has been an increase in interest from the aspects of transshipment and connection between the means of transportation. Not only for passengers but also for freight transportation as the need for transportation efficiency is growing while the importance of logistic railway transportation is emerging. The domestic freight transportation is carried out by roads, railroads, ships, and port. However, as other means of transportation, except road, is impossible for Door to Door Service, multimodal transportation accompanied by road transportation is carried out. Here, even though 'transshipment' occurs, because of the lack of basic data regarding this, it is difficult to reflect it in the demand forecasting. With respect to the Korean freight O-D, it was very difficult to have equivalent comparison on the competitiveness and availability of transportation services between the point of departure and the final destination. Taking into account the study of implementation of logit model considering the time and cost of transshipment of multimodal transportation and the transshipment resistance value upon selecting means of freight transportation on multimodal transportation was comparatively insufficient. This study consisted of questionnaire targeting shippers, and based on this, transshipment resistance value was calculated by deriving utility function. By doing so, I intend to examine the effect 'transshipment' has on selecting the means of transportation occurring from freight transportation.

• Journal of Korean Institute of Industrial Engineers
• /
• v.3 no.1
• /
• pp.39-47
• /
• 1977

Most of the current literature on inventory theory has been devoted to the study of single stage models. A class of inventory problems which is of great interest is the multistage inventory system which involves a series and hierarchical sequence of stations. This study analyzes some aspect of the series type and multi-stage inventory system, using the fixed cycle ordering which bas a modificatory control function in the system equations. The objective of this study is to clarify the dynamic behavior of the system. The author has derived the theoretical formulas of variation of ordering quantity and stock fluctuation of each stage due to power spectral density function. Influence of parameters such as, (1) intensity of autocorrelation of demand sequence ($\lambda$), (2) forecasting exponential smoothing factors of each stage (${\alpha}_1,\;{\alpha}_2,\;{\alpha}_3$) and (3) production control factor of the 3rd stage ($\gamma$), as operators of the system on the variation of ordering quantity and stock fluctuation of the system. is also clarified. As a result of this study, the relations between the variation of ordering quantity, stock fluctuation and the parameters of the system, have been found. The principles and the theorical analysis presented here will be applicable to more complex type of discrete control systems in constructing the specific condition of the system to minimize inventory variances.