• Title/Summary/Keyword: Real-Time Forecasting System

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Development of an Event Rainfall-Runoff Model in Small Watersheds

  • Lee, Sang-Ho;Lee, Kil-Seong
    • Korean Journal of Hydrosciences
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    • v.6
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    • pp.81-98
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    • 1995
  • A linear reservoir rainfall-runoff system was developed as a rainfall-runoff event simulation model. It was achieved from large modification of runoff function method. There are six parameters in the model. Hydrologic losses consist of some quantity of initial loss and some ratio of rainfall intensity followed by initial loss. The model has analytical routing equations. Hooke and Jaeves algorithm was used for model calibration. Parameters were estimated for flood events from '84 to '89 at Seomyeon and Munmak stream gauges, and the trends of major parameters were analyzed. Using the trends, verifications were performed for the flood event in September 1990. Because antecedent rainfalls affect initial loss, future researches are required on such effects. The estimation method of major parameters should also be studied for real-time forecasting.

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A Study on the need for a Digital Twin-based Real-time Flood Forecasting and Alarm Monitoring System (디지털 트윈 기반 실시간 침수 예·경보 모니터링 시스템 필요성 연구)

  • Kim, Young-Hwi;Tian-Feng Yuan
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2022.10a
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    • pp.421-422
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    • 2022
  • 최근 들어 집중호우와 긴 장마기간으로 인해 침수피해가 많이 발생하고 있다. 행정안전부 재해연보 2020에 따르면, 2020년 자연 재난 피해액 중 83%인 1조 952억이 호우로 인한 피해로 집계 되었다. 국내의 하수 관로 설계는 관로와 맨홀등의 용량을 검토하는 1차원 해석으로 수행 하지만, 재난 시는 설계에서 예측한 강우량 이상이 발생하고 월류한 물의 영향을 분석하기 위해서는 2차원 해석이 필요하다. 따라서 본 연구에서는 2차원 해석 기반의 모의 침투해석을 기반으로 풍수해저감대책의 대응대책인 침수 예·경보 모니터링 시스템을 구축 한 국내·외 사례를 분석하고 필요성에 대해서 알아보도록 한다.

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Expressway Travel Time Prediction Using K-Nearest Neighborhood (KNN 알고리즘을 활용한 고속도로 통행시간 예측)

  • Shin, Kangwon;Shim, Sangwoo;Choi, Keechoo;Kim, Soohee
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.6
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    • pp.1873-1879
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    • 2014
  • There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

Forecasting of Real Time Traffic Situation using Neural Network and Sensor Database Management System (신경망과데이터베이스 관리시스템을 이용한 실시간 교통상황 예보)

  • Jin, Hyun-Soo
    • Proceedings of the KAIS Fall Conference
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    • 2008.05a
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    • pp.248-250
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    • 2008
  • This paper proposes a prediction method to prevent traffic accident and reduce to vehicle waiting time using neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dose not consider coordinating green time. Moreover, we present neural network approach for traffic accident prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data. Computer simulation results proved reducing traffic accident waiting time which proposed neural network better than conventional system dosen't consider neural network.

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Smart Disaster Safety Management System for Social Security (사회안전을 위한 스마트 재난안전관리 시스템)

  • Kang, Heau-jo
    • Journal of Digital Contents Society
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    • v.18 no.1
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    • pp.225-229
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    • 2017
  • In this paper, various units of industrial disaster safety threats as well as local and national facilities unit real-time detection and prevention refer to the corresponding system goes into disaster management preparedness, prevention, response recovery of phase I systematic ICT skills that can be managed more efficiently. In addition, the immediate disaster prevention and preparedness for early forecasting preemptive damage scale and high-tech information exchange technology to overcome the limitations of a human disaster in the field against the analysis and strategy of preemptive disaster safety management with smart risk management and prevention in response and recovery and the scene quickly and efficient mutual cooperation and effective collaboration and cooperation of the Community Center social security presented a smart disaster safety management system.

Monitoring Flood Disaster Using Remote Sensing Data

  • Chengcai, Zhang;Xiuwan, Chen;Gaolong, Zhu;Wenjiang, Zhang;Peng, Sun-Chun
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.280.2-286
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    • 1998
  • Flood is the main natural disaster mostly in the world. It is a care problem to prevent flood disaster generally. The frequency of flood disaster is high and the distributing field is wide, the 50 percent population and 70 percent properties distribute at the threaten field of flood disaster in China. Flood disaster has caused a huge amount of economical losses and these losses have an increasing trend. Along with the development of reducing natural disaster action, it has become one of the most attentive problems for monitoring flood, preventing flood and forecasting flood efficiently. Remote sensing has the characteristics of large spatial observing areas, wide spectrum ranges, and imaging far away from the targets, imaging capabilities all weather. Spatial remote sensing information, which records the full, processes of the disaster's occurrence and development in real-time. It is a scientific basis for management, planning and decision-making. Through systemic analyzing the RS monitoring theory, based on compounding RS information, the technology and method of monitoring flood disaster are studied.

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Computation of the Shortest distance and Forecasting movement distance for Y/T Multi-Cycle System (Multi-Cycle 작업을 위한 Y/T 최단거리 및 예상 이동거리 계산)

  • Park, Tae-jin;Kim, Han-soo;Kim, Cheeyong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.127-130
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    • 2009
  • In this paper, we introduce a Y/T(Yard Tractor) Multi-Cycle System on the basis of RTLS that improves a low efficient loading and unloading. In the proposed approach, we apply the best suited algorithm looking for seeking of the optimum path and the shortest movement distance. In this paper, Our experiment results show that rate of a driving distance is reduced more than 12% compared to the average value, and that is reduced more than 23% compared to the maximum value.

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A study on the efficient early warning method using complex event processing (CEP) technique (복합 이벤트 처리기술을 적용한 효율적 재해경보 전파에 관한 연구)

  • Kim, Hyung-Woo;Kim, Goo-Soo;Chang, Sung-Bong
    • 한국정보통신설비학회:학술대회논문집
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    • 2009.08a
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    • pp.157-161
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    • 2009
  • In recent years, there is a remarkable progress in ICTs (Information and Communication Technologies), and then many attempts to apply ICTs to other industries are being made. In the field of disaster managements, ICTs such as RFID (Radio Frequency IDentification) and USN (Ubiquitous Sensor Network) are used to provide safe environments. Actually, various types of early warning systems using USN are now widely used to monitor natural disasters such as floods, landslides and earthquakes, and also to detect human-caused disasters such as fires, explosions and collapses. These early warning systems issue alarms rapidly when a disaster is detected or an event exceeds prescribed thresholds, and furthermore deliver alarm messages to disaster managers and citizens. In general, these systems consist of a number of various sensors and measure real-time stream data, which requires an efficient and rapid data processing technique. In this study, an event-driven architecture (EDA) is presented to collect event effectively and to provide an alert rapidly. A publish/subscribe event processing method to process simple event is introduced. Additionally, a complex event processing (CEP) technique is introduced to process complex data from various sensors and to provide prompt and reasonable decision supports when many disasters happen simultaneously. A basic concept of CEP technique is presented and the advantages of the technique in disaster management are also discussed. Then, how the main processing methods of CEP such as aggregation, correlation, and filtering can be applied to disaster management is considered. Finally, an example of flood forecasting and early alarm system in which CEP is incorporated is presented It is found that the CEP based on the EDA will provide an efficient early warning method when disaster happens.

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Impact of High-Resolution Sea Surface Temperatures on the Simulated Wind Resources in the Southeastern Coast of the Korean Peninsula (고해상도 해수면온도자료가 한반도 남동해안 풍력자원 수치모의에 미치는 영향)

  • Lee, Hwa-Woon;Cha, Yeong-Min;Lee, Soon-Hwan;Kim, Dong-Hyeok
    • Journal of Environmental Science International
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    • v.19 no.2
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    • pp.171-184
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    • 2010
  • Accurate simulation of the meteorological field is very important to assess the wind resources. Some researchers showed that sea surface temperature (SST) plays a leading role on the local meterological simulation. New Generation Sea Surface Temperature (NGSST), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Real-Time Global Sea Surface Temperature (RTG SST) have different spatial distribution near the coast and OSTIA shows the best accuracy compared with buoy data in the southeastern coast of the Korean Peninsula. Those SST products are used to initialize the Weather Research and Forecasting (WRF) Model for November 13-23 2008. The simulation of OSTIA shows better result in comparison with NGSST and RTG SST. NGSST shows a large difference with OSTIA in horizontal and vertical wind fields during the weak synoptic condition, but wind power density shows a large difference during strong synoptic condition. RTG SST shows the similar patterns but smaller the magnitude and the extent.

Trend Analysis and Diagnosis for BWTS Remote Monitoring (BWTS 원격 모니터링을 위한 트렌드 분석 및 진단)

  • Choi, Wook-Jin;Kim, Chin-Hoon;Choi, Hwi-Min;Lee, Kwang-Seob;Choi, Woo-Jin;Kim, Joo-Man
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.3
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    • pp.127-135
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    • 2014
  • On lot of ships, Ballast Water Treatment Systems(BWTS) are in use, or the newly built ship should be mandatory installation by 2017. It is IMO(International Maritime Organization) regulations. Because the vessel is in long distance, It is managed this system only in the vessel and it may occur considerable cost of maintenance when a problem arises from BWTS. We describe in this paper how to monitor treated ballast water to make sure the ballast water and BWTS on a ship is in proper condition, but before the port entrance. In addition, analysing and forecasting trend signal to prevent failure. Also we can expect reduce the cost of BWTS maintenance. We can monitor the sensor data value's change which collected through satellite from BWTS. And we can observate the ballasting and de-ballasting state of the vessel easily.