• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.473-482
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• 2015

Doppler weather radar is an important tool for meteorological research. Through several decades of development, Doppler weather radar has enormous progress in understanding, detection and warning of meso and micro scale weather system. It makes a significant contribution to weather forecast and weather disaster warning. But the large amount of data process limits the application of Doppler weather radar. This paper proposed for fast weather radar data processing based on CUDA. CDUA is a powerful platform for highly parallel programming developed by NVIDIA. Through running plenty of threads, radar data can be calculated at same time. In experiment, CUDA parallel program can significantly improve weather data processing time.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.76-92
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• 2018

This study aimed to establish database of rainfall inundation area by rainfall scenarios and conduct a real time prediction for urban flood mitigation. the data leaded model was developed for the mapping of inundated area with rainfall forecast data provided by korea meteorological agency. for the construction of data leaded model, 1d-2d modeling was applied to Gangnam area, where suffered from severe flooding event including september, 2010. 1d-2d analysis result agree with observed in term of flood depth. flood area and flood occurring report which maintained by NDMS(national disaster management system). The fitness ratio of the NDMS reporting point and 2D flood analysis results was revealed to be 69.5%. Flood forecast chart was created using pre-flooding database. It was analyzed to have 70.3% of fitness in case of flood forecast chart of 70mm, and 72.0% in case of 80mm flood forecast chart. Using the constructed pre-flood area database, it is possible to present flood forecast chart information with rainfall forecast, and it can be used to secure the leading time during flood predictions and warning.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.109-120
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• 2010

Heat wave is a disaster, which increases morbidity and mortality in temperate regions. Climate model results indicate that both intensity and frequency of heat wave in the future will be increased. This study shows the result about relationship between excess mortality and offensive airmass in 7 metropolitan cities, and an operational Heat-Health Warning System (HHWS) in Korea. Using meteorological observations, the Spatial Synoptic Classification (SSC) has been used to classify each summer day from 1982 to 2007 into specific airmass categories for each city. Through the comparative study analysis of the daily airmass type and the corresponding daily mortality rate, Dry Tropical (DT), and Moist Tropical plus (MT+) were identified as the most offensive airmasses with the highest rates of mortality. Therefore, using the multiple linear regression, forecast algorithm was produced to predict the number of the excess deaths that will occur with each occurrence of the DT and MT+ days. Moreover, each excess death forecast algorithm was implemented for the system warning criteria based on the regional acclimatization differences. HHWS will give warnings to the city's residents under offensive weather situations which can lead to deterioration in public health, under the climate change.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.101.2-101.2
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• 2011

We have developed solar and space weather monitoring system for space weather users since 2007 as a project named 'Construction of Korea Space Weather Prediction Center'. In this presentation we will introduce space weather monitoring system for Geostationary Satellites and Polar Routes. These were developed for satisfying demands of space weather user groups. 'Space Weather Monitoring System for Geostationary Satellites' displays integrated space weather information on geostationary orbit such as magnetopause location, nowcast and forecast of space weather, cosmic ray count rate, number of meteors and x-ray solar flux. This system is developed for space weather customers who are managing satellite systems or using satellite information. In addition, this system provides space weather warning by SMS in which short message is delivered to users' cell phones when space weather parameters reach a critical value. 'Space Weather Monitoring System for Polar Routes' was developed for the commercial airline companies operating polar routes. This provides D-region and polar cap absorption map, aurora and radiation particle distribution, nowcast and forecast of space weather, proton flux, Kp index and so on.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.743-750
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• 2008

Due to unusual climate change and global warming, drought and flood happen frequently not only in Korea but also in all over the world. It leads to the serious damages and injuries in urban areas as well as rural areas. Since the concentration time is short and the flood flows increase urgently in urban stream basin, the chances of damages become large once heavy storm occurs. A decision support system for flood forecasting and warning in urban stream is developed as an alternative to alleviate the damages from heavy storm. It consists of model base management system based on ANFIS (Adaptive Neuro Fuzzy Inference System), database management system with real time data building capability and user friendly dialog generation and management system. Applying the system to the Tanceon river basin, it can forecast and warn the stream flows from the heavy storm in real time and alleviate the damages.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1427-1431
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• 2007

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.669-673
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• 2008

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.61-74
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• 2021

Agriculture is most closely related to weather, and the government pursues stable food production by weather research. However, abnormal weather conditions have occurred frequently around the world in recent years, and stable food production has been threatened. Among them, heavy snow in winter tends to increase in frequency and size, which causes serious damage to greenhouses. Therefore, it is imperative to build a system reflecting various demands to reduce the damage to agricultural facilities caused by heavy snow. A business model can realize this as a way of commercialization, however, no suitable model has been presented to date. Therefore, this study aims to design a representative business model that can establish a safety system by distributing a greenhouse disaster prevention warning system for heavy snow to farms.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.131-138
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• 2009

In this paper, a dynamic warning system to forecast inland flooding associated with typhoons and storms is described. The system is used operationally during the typhoon season to anticipate the potential impact such as inland flooding on the coastal zone of interest. The system has been developed for the use of the public and emergency management officials. Simple typhoon models for quick prediction of wind fields are implemented in a user-friendly way by using a Graphical User Interface (GUI) of MATLAB. The main program for simulating tides, depth-averaged tidal currents, wind-driven surges and currents was also vectorized for the fast performance by MATLAB. By pushing buttons and clicking the typhoon paths, the user is able to obtain real-time water level fluctuation of specific points and the flooding zone. This system would guide local officials to make systematic use of threat information possible. However, the model results are sensitive to typhoon path, and it is yet difficult to provide accurate information to local emergency managers.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1968-1970
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• 2003

In this paper we propose a system to forecast the dangerous behavior of the dementia patients. Basic idea of our approach is to measure the body movements of the dementia patients using the acceleration sensor. Based on the data measured, warning the care-givers about possible dangerous actions like falling down from the bed and slipping down onto the floor to some extent. The signals measured by the acceleration sensor are processed by a one-chip computer. Based on the diagnosis of the one-chip computer , alert signal is generated to the care-giver by a wire-less signal. The sensor is implemented in a compact body . Applicability of the system is now being examined at a nursing home.