• 한국안전학회지
• /
• 제27권4호
• /
• pp.108-114
• /
• 2012

Traffic Accident Merging Index(TAMI) is developed for TMACS(Traffic Safety Information Management Complex System). TAMI is calculated by combining 'Severity Index' and 'Frequency'. This paper suggest the accurate TAMI prediction model by time series forecasting. Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. Searches the model which minimizes the error of 230 local self-governing groups. TAMI of 2007~2009 years data predicts TAMI of 2010. And TAMI of 2010 compares an actual index and a prediction index. And the error is minimized the constant where selects. Exponential Smoothing model was selected. And smoothing constant was decided with 0.59. TAMI Forecasting model provides traffic next year safety information of the local government.

• Water Engineering Research
• /
• 제3권2호
• /
• pp.123-134
• /
• 2002

A developed Quantitative Flood Forecasting (QFF) model was applied to the mid-Atlantic region of the United States. The model incorporated the evolving structure and frequency of intense weather systems of the study area for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters associated with synoptic atmospheric conditions as Input. Here, we present results from the application of the Quantitative Flood Forecasting (QFF) model in 2 small watersheds along the leeward side of the Appalachian Mountains in the mid-Atlantic region. Threat scores consistently above 0.6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 40% and up to 55 % were obtained.

• 한국간호교육학회지
• /
• 제15권2호
• /
• pp.251-259
• /
• 2009

Purpose: Climate change affects human health and calls for a health forecasting service. The purpose of this study was to explore the students' actual use and their satisfaction with meteorological information and the demands on health forecasting at a university in South Kyungsang Province. Method: This study used a descriptive design through structured self-report questionnaires including frequency, contents, purpose, perception, satisfaction of meterological information and need and demand of health forecasting. Data were collected from June 1 to 5, 2009 and analyzed using the SPSS 17.0 program. Descriptive statistics, t-test, ANOVA, $\chi^2$ test and Person's correlation coefficient were used to analyze the data. Result: The majority of the students watched the daily weather information to decide about daily work, outdoor activity or habitually. The mean score of need for health forecasting was $3.44{\pm}.81$, and the demand for health forecasting was $2.93{\pm}1.05$. Significant differences were found in the need for health forecasting according to sex, major, and environmental disease. In addition, the higher the satisfaction of health forecasting, the higher the demand for it. Conclusion: I suggest improving the meteorological information system technically and developing a health forecasting service resulting in a healthier and more comfortable life.

• Water Engineering Research
• /
• 제3권2호
• /
• pp.113-122
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as lifetime, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.

• 경영과학
• /
• 제25권1호
• /
• pp.29-41
• /
• 2008

In the mobile communication service market, this study represents an attempt to forecast the subscribers of the IMT-2000 service market using the questionnaire of experts which is the qualitative technique is used. In this study, by using the substitution model of next generations among products in order to analyze the IMT-2000 demand of service, a demand was predicted. And by estimating the market demand prospect in which it becomes the important factor of the IMT-2000 service diffusion according to each bandwidth frequency the politically necessary approaching direction about the frequency was presented. It will be able to become the important part to not only the business carrier but also the policy maker to examine a prospect toward the subscriber of the IMT-2000 service. As a result, the market demand was exposed to be most big when the SKT 800MHz, and the KTF 800(900)MHz were used as the additional frequency. And it was likely to reach to the IMT-2000 number of subscribers to about 35.750 thousand peoples in the future at 2015.

• Journal of Information Technology Applications and Management
• /
• 제20권4호
• /
• pp.221-234
• /
• 2013

In this paper, we report bankruptcy risk level forecasting result for automobile parts manufacturing industry. With the premise that upstream supply risk and downstream demand risk could impact on automobile parts industry bankruptcy level in advance, we draw upon industry input-output table to use the economic indicators which could reflect the extent of supply and demand risk of the automobile parts industry. To verify the validity of each economic indicator, we applied simple linear regression for each indicators by varying the time lag from one month (t-1) to 12 months (t-12). Finally, with the valid indicators obtained through the simple regressions, the composition of valid economic indicators are derived using stepwise linear regression. Using the monthly automobile parts industry bankruptcy frequency data accumulated during the 5 years, R-square values of the stepwise linear regression results are 68.7%, 91.5%, 85.3% for the 3, 6, 9 months time lag cases each respectively. The computational testing results verifies the effectiveness of our approach in forecasting bankruptcy risk forecasting of the automobile parts industry.

• 한국방재학회:학술대회논문집
• /
• 한국방재학회 2008년도 정기총회 및 학술발표대회
• /
• pp.405-408
• /
• 2008

Up to now, a lot of houses, roads and other urban facilities have been damaged by natural disasters such as flash floods and landslides. It is reported that the size and frequency of disasters are growing greatly due to global warming. In order to mitigate such disaster, flood forecasting and alerting systems have been developed for the Han river, Geum river, Nak-dong river and Young-san river. These systems, however, do not help small municipal departments cope with the threat of flood. In this study, a real-time urban flood forecasting service (U-FFS) is developed for ubiquitous computing city which includes small river basins. A test bed is deployed at Tan-cheon in Gyeonggido to verify U-FFS. It is found that U-FFS can forecast the water level of outlet of river basin and provide real-time data through internet during heavy rain. Furthermore, it is expected that U-FFS presented in this study can be applied to ubiquitous computing city (u-City) and/or other cities which have suffered from flood damage for a long time.

• 한국의류산업학회지
• /
• 제22권5호
• /
• pp.551-560
• /
• 2020

Due to the nature of fashion design that responds quickly and sensitively to changes, accurate forecasting for upcoming fashion trends is an important factor in the performance of fashion product planning. This study analyzed the major phenomena of fashion trends by introducing text mining and a big data analysis method. The research questions were as follows. What is the key term of the 2010SS~2019FW fashion trend? What are the terms that are highly relevant to the key trend term by year? Which terms relevant to the key trend term has shown high frequency in news articles during the same period? Data were collected through the 2010SS~2019FW Pre-Trend data from the leading trend information company in Korea and 45,038 articles searched by "fashion+material" from the News Big Data System. Frequency, correlation coefficient, coefficient of variation and mapping were performed using R-3.5.1. Results showed that the fashion trend information were reflected in the consumer market. The term with the highest frequency in 2010SS~2019FW fashion trend information was material. In trend information, the terms most relevant to material were comfort, compact, look, casual, blend, functional, cotton, processing, metal and functional by year. In the news article, functional, comfort, sports, leather, casual, eco-friendly, classic, padding, culture, and high-quality showed the high frequency. Functional was the only fashion material term derived every year for 10 years. This study helps expand the scope and methods of fashion design research as well as improves the information analysis and forecasting capabilities of the fashion industry.

• 한국정보통신설비학회:학술대회논문집
• /
• 한국정보통신설비학회 2007년도 학술대회
• /
• pp.181-184
• /
• 2007

Up to now, a lot of houses, roads and other urban facilities have been damaged by natural disasters such as flash floods and landslides. It is reported that the size and frequency of disasters are growing greatly due to global warming. In order to mitigate such disaster, flood forecasting and alerting systems have been developed for the Han river, Geum river, Nak-dong river and Young-san river. These systems, however, do not help small municipal departments cope with the threat of flood. In this study, a real-time urban flood forecasting service (U-FFS) is developed for ubiquitous computing city which includes small river basins. A test bed is deployed at Tan-cheon in Gyeonggido to verify U-FFS. Wireless sensors such as rainfall gauge and water lever gauge are installed to develop hydrologic forecasting model and CCTV camera systems are also incorporated to capture high definition images of river basins. U-FFS is based on the ANFIS (Adaptive Neuro-Fuzzy Inference System) that is data-driven model and is characterized by its accuracy and adaptability. It is found that U-FFS can forecast the water level of outlet of river basin and provide real-time data through internet during heavy rain. It is revealed that U-FFS can predict the water level of 30 minutes and 1 hour later very accurately. Unlike other hydrologic forecasting model, this newly developed U-FFS has advantages such as its applicability and feasibility. Furthermore, it is expected that U-FFS presented in this study can be applied to ubiquitous computing city (U-City) and/or other cities which have suffered from flood damage for a long time.

• 대한교통학회지
• /
• 제18권3호
• /
• pp.55-76
• /
• 2000

실시간 통행시간관련자료의 집계시간간격은 보다 신뢰성있는 통행시간정보제공과 교통정보센터의 효율적인 운영을 위해 매우 중요한 요소이다. 그러나 대부분의 기존 VDS 및 TCS교통정보 데이터는 통계학적·공학적 차원에서의 합리적인 연구나 검증없이 경험적 간격으로 집계되고 있다. 본 연구의 목적은 링크 및 교통축(Corridor) 통행시간 산정 및 예측시의 최적 집계 시간간격을 결정할 수 있는 통계학적 모형을 개발하고 실제 도로망에서 수집되는 통행시간자료에 적용하는 것이다 첫째로, 본 연구는 링크 및 교통축 통행시간 산정 및 예측으로 인한 오차를 계량화하는 통계학적 모형을 제시하고, 제시된 모형의 의미를 교통류이론 측면과 통행시간정보 이용자측면에서 살펴보았다. 둘째로, 미국 Texas, Houston의 도시고속도로에서 AVI시스템을 통해 수집된 통행시간자료를 제시된 모형에 적용하였다. 적용결과 링크통행시간 산정을 위한 최적 집계시간간격보다 링크통행시간예측을 위한 최적 집계시간간격이 큰 것으로 나타났으며, 교통축 통행시간 산정 및 예측을 위한 최적 집계시간간격은 교통축을 구성하는 링크간의 상관관계 (Correlation)에 큰 영향을 받는 것으로 분석되었다.