• Journal of the Korean Society of Costume
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• v.18
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• pp.321-337
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• 1992

Fashions are constantly subject to change, so that forecasting trends in fashion is very difficult and the forecasting is very important. The reason is that forecasting is identifying a hot trend for the next days' business and projecting the future. The purpose of this study is to suggest the realistic forecasting theory identify fashion trends at present, further forecast fashion trends to 1995. For this study, historical models (th historical resurrection model, the historical continuity model) and the art movement model among the behavioral science models which was suggested in 1986 by Geoge B.Sproles were selected. According to this study, was exhibited. This curve was resulted from relation between 1980s fashion trends and the behavioral science models of fashion. Fashion trends to 1995 through will be followings; 1. Body Conscious look as one of the characteristics of modern fashion will bi continued throughout 1990s' fashion trends. 2. The attraction of Mini style was started from the middle of 1980s, recently gets near micro mini and super shouts, These are representative of the historical continuity model. 3. Mini look as revivals of '60s in early 1990s fashion trends. This phenomenon identifies that "Fashion is repetition" 4. When Mini look and super shorts reach, will not progress any more. In this time, will bi seen transfer of style be using classic style. Tat is modern classic will be appeared. also this condition is same from late 1960s to early 1970s. In view of the historical base, the action of the varieted pants will be prominent. 5. Fashion trends which passed through this process will transfer from young look to elegant look. In this time, designers will retrospect '30s and '50s fashion trends, and then will design modern feminine look. 6. Ethnic look, the fashion trend after that condition will be accelated feminine look. This look with the feminine look will reveal rich, colorful, elegance feminine image. 7. In 1980s, activity and function in clothes were demanded. The clothes which are considered these condition will be demanded continuously. 8. The variety of fashion will appear as mixmode and new coordinate look in a clothes simultaneously in fashion of '90s. And these looks will creat mixed beauty. 9. Pop art, op art, graphic art will be not only development of textile but also movement of fashion soul in 1990s. The fashion behavior will be continuously scientificated.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.421-436
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• 2016

Public-Private-Partnerships tend to be committed high project development cost and recover the cost through future revenue during the operation period. In general, long-term concession can bring on more revenue to private investors, but short-term concession less revenue due to the short recovering opportunities. The concession period is usually determined by government in advance or by the private sectors's proposal although it is a very crucial factor for the PPPs. Accurate traffic forecasting should be most important in planing and evaluating the operation period in that the forecasted traffic determines the project revenue with user fees in PPPs. In this regards, governments and the private investors are required to consider the traffic forecast risk when determining concession period. This study proposed a model for the optimal concession period in the PPPs transportation projects. Monte Carlo simulation was performed to find out the optimal concession period while traffic forecast uncertainty is considered as a project risk under the expected return of the private sector. The simulation results showed that the optimal concession periods are 17 years and 21 years at 5.5% and 7% discount level, respectively. This study result can be applied for the private investors and/or any other concerned decision makers for PPPs projects to set up a more resonable concession period.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.13-21
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• 2007

Recently, very short-term rainfall forecast using radar is required for regional flash flood according to climate change. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. Vflo model which was developed Oklahoma university was used as physical based distributed model, and Namgang dam watershed ($2,293km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using K-RainVieux, preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model(Vflo). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.1-22
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• 2020

The global container terminal market is predicted to see continued future volume growth. According to Drewry, global container shipments rose by 6.3% year-on-year to 750 billion twenty-foot equivalent units (TEUs) in 2017 and are forecast to experience continued growth to 9.3 billion TEUs in 2022. According to IHS Markit, the global terminal operator (GTO) market is forecast to grow more than 10% annually, up from $2.4 billion in 2017, to exceed $3 billion by 2022. However, Hyundai Merchant Marine is the only real GTO in Korea. In particular, the shipping and port markets are facing drastic changes, both at home and abroad, including a slowdown in the growth of domestic export and import shipments, environmental changes in the container market caused by the trade frictions between the US and China, and increased changes in container shipments caused by the trade frictions between Korea and Japan. In this study, we propose ways for domestic companies to participate in the continuously growing GTO market. After analyzing the current status of the global GTO market, the government expressed a desire to explore ways to establish GTOs through the Port Authority and the Korea Ocean Business Corporation. Therefore, four types of establishment plans were proposed, along with a legal framework for the establishment of GTOs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.521-528
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• 2016

The tollbooths of a main motorway toll plaza are usually operated proactively responding to the variations of traffic demands of two-type vehicles, i.e. cars and the other (heavy) vehicles, respectively. In this vein, it is one of key elements to forecast accurate traffic volumes for the two vehicle types in advanced tollgate operation. Unfortunately, it is not easy for existing univariate short-term prediction techniques to simultaneously generate the two-vehicle-type traffic demands in literature. These practical and academic backgrounds make it one of attractive research topics in Intelligent Transportation System (ITS) forecasting area to forecast the future traffic volumes of the two-type vehicles at an acceptable level of accuracy. In order to address the shortcomings of univariate short-term prediction techniques, a Multiple In-and-Out (MIO) forecasting model to simultaneously generate the two-type traffic volumes is introduced in this article. The MIO model based on a non-parametric approach is devised under the on-line access conditions of large-scale historical data. In a feasible test with actual data, the proposed model outperformed Kalman filtering, one of a widely-used univariate models, in terms of prediction accuracy in spite of multivariate prediction scheme.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.397-405
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• 2015

In the past, expressways focused on mobility. However, the paradigm of expressways fuction today has been changed from fast expressways to safe expressways as people's quality of living and consciousness level heightened. In 2012, 3,550 traffic accidents occurred on expressways and 371 people died. The fatality rate of traffic accidents on expressways is almost twice that on general national roads. This study developed accident forecast models (safety performance functions) based on the number of traffic accidents and traffic volumes on six major lines on expressways. It is difficult to forecast safety performance functions for each expressway line because the lines and the scales of expressways are different from each other; therefore, integrated safety performance functions of six lines were determined first, and the coefficients, which can correct the traffic accidents on each line, were calculated. It is believed that this study will contribute in the safer management of expressways by being used as basic information in the establishment of traffic safety strategies for each expressway line in prevention of traffic accidents. Moreover, more studies would be required in the future, which would suggest reliable accident forecasts by calculating correction coefficients by line through integrated models by groups dependent on the characteristics of each line.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.71-79
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• 2011

Traditionally, a dynamic network model is considered as a tool for solving real-time traffic problems. One of useful and practical ways of using such models is to use it to produce and disseminate forecast travel time information so that the travelers can switch their routes from congested to less-congested or uncongested, which can enhance the performance of the network. This approach seems to be promising when the traffic congestion is severe, especially when sudden incidents happen. A consideration that should be given in implementing this method is that travel time information may affect the future traffic condition itself, creating undesirable side effects such as the over-reaction problem. Furthermore incorrect forecast travel time can make the information unreliable. In this paper, a network-wide travel time prediction model under incidents is developed. The model assumes that all drivers have access to detailed traffic information through personalized in-vehicle devices such as car navigation systems. Drivers are assumed to make their own travel choice based on the travel time information provided. A route-based stochastic variational inequality is formulated, which is used as a basic model for the travel time prediction. A diversion function is introduced to account for the motorists' willingness to divert. An inverse function of the diversion curve is derived to develop a variational inequality formulation for the travel time prediction model. Computational results illustrate the characteristics of the proposed model.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.385-391
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• 2000

Recently, neural network research for forecasting the consecutive controlling rules of the future is being progressed, using the series data which are different from the traditional statistical analysis methods. In this paper, we suggest the pruning algorithm for the fast and exact weather forecast that excludes the hidden layer of the early optional designed nenral network. There are perform the weather forecast experiments using the 22080 kinds of weather data gathered from 1987 to 1996 for proving the efficiency of this suggested algorithm. Through the experiments, the early optional composed $26{\times}50{\times}1$ nenral network became the most suitable $26{\times}2{\times}1$ structure through the pruning algorithm suggested, in the optimum neural network $26{\times}2{\times}1$, in the case of the error temperature ${\pm}0.5^{\circ}C$, the average was 33.55%, in the case of ${\pm}1^{\circ}C$, the average was 61.57%, they showed more superior than the average 29.31% and 54.47% of the optional designed structure, also. we can reduce the calculation frequency more than maximum 25 times as compared with the optional sturcture neural network in the calculation frequencies.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.155-162
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• 2009

The recent increase of light rail construction by the private sector in Korea has caused a new issue in forecasting rail demand. Integrated fare systems between several rail operators is convenient and brings cost savings to users, and therefore is also very effective in increasing demand. However, it causes some short-term revenue loss to operators so that the private sector often suggests a non-integrated fare system. The current rail demand forecasting model is based upon an integrated fare system. Thus this model cannot be used to forecast the demand with a non-integrated fare system. Some value of transfer fare should be estimated and applied to forecast the demand in a non-integrated fare system. This study conducted a stated preference (SP) survey on urban railway passengers and estimated the value of transfer fare. The estimated value is 2,609 Won/hr, which is about 52% of in-vehicle time. This shows railway users have a tendency to pay more for transfer fares to save time or distance. This value has some limitations since it is derived from the SP survey. If some non-integrated fare system is applied in the future and a RP survey is conducted and compared with these study results, a more clear value of the transfer fare will be derived.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.1-11
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• 2021

Recently, in Korea, the risk of meteorological disasters is increasing due to climate change, and the damage caused by rainfall is being emphasized continuously. Although the current weather forecast provides quantitative rainfall, there are several difficulties in predicting the extent of damage. Therefore, in order to understand the impact of damage, the threshold rainfall for each watershed is required. The damage caused by rainfall occurs differently by region, and there are limitations in the analysis considering the characteristic factors of each watershed. In addition, whenever rainfall comes, the analysis of rainfall-runoff through the hydrological model consumes a lot of time and is often analyzed using only simple rainfall data. This study used GIS data and calculated the threshold rainfall from the threshold runoff causing flooding by coupling two hydrologic models. The calculation result was verified by comparing it with the actual case, and it was analyzed that damage occurred in the dangerous area in general. In the future, through this study, it will be possible to prepare for flood risk areas in advance, and it is expected that the accuracy will increase if machine learning analysis methods are added.