• 한국방재안전학회논문집
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• 제6권1호
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• pp.19-27
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• 2013

자연재해로 인한 재산 및 인명피해는 재해 유형별 사전 정보와 예방활동을 수행함으로 그 피해를 최소화 할 수 있다는 점에서 재해 예 경보시스템의 중요성이 강조되고 있다. 따라서 본 연구에서는 태풍, 홍수, 폭설 등 자연재해 관련 예 경보의 유형과 정보 전달 매체 및 재해 예 경보 전달 체계 현황과 실태 등을 분석하고 첨단정보 통신기술과 방송 통신의 융합에 대한 기술대안 분석으로서 국가적 통합 경보전달 체계 구축의 시급성을 제시하였다. 또한 재해 예 경보 시스템간의 유기적인 연계를 통하여 각각의 시설 간에 중복 설치를 사전에 방지하는 한편 방재정보의 표준화를 바탕으로 예 경보의 종합적이고 체계적인 관리와 운영을 위한 전문성을 갖춘 전담조직의 상설화 등을 통해 재해 예 경보 시스템의 효율성 제고방안을 연구한 논문이다.

• 한국농공학회논문집
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• 제57권4호
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• pp.135-141
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• 2015

The objective of this study is to develop an early warning system for rainfall induced landslides. For this study, we suggested an analysis process using rainfall forecast data. 1) For a selected slope, safety factor with saturated depth was analyzed and safety factor threshold was established (warning FS threshold=1.3, alarm FS threshold=1.1). 2) If rainfall started, saturated depth and safety factor was calculated with rainfall forecast data, 3) And every hour after safety factor is compared with threshold, then warning or alarm can issued. In the future, we plan to make a early warning system combined with the in-situ inclinometer sensors.

• 전자공학회논문지A
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• 제29A권11호
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• pp.25-39
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• 1992

Due to the data processing development by the computer, the early warning system recently has made a remarkable evolution in its functions and performance as a component of the communication and control system which is also supported by the computer communication and intelligence system. In this paper it is presented that a integrated data processing system is designed to integrate the information sent from the various radar systems which constitute an early warning system. The suggested system model of this paper is devided into two types of structures, the centralized model and the distributed model, according to the data processing algorithm. We apply the queueing theory to analyse the performance of the designed models and the OPNET system kernel to make the analysing program with C language. From the analysis of the queueing components by applying the analysis programs to the designed systems, we got the tendancies and characteristics of both models, that is, a fast data processing performance of the distributed model and a stable data processing capability of the centralized model.

• 한국콘텐츠학회논문지
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• 제9권12호
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• pp.504-514
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• 2009

최근 문화재나 시설물 관리를 위한 화재 감시 응용 시스템에 대한 요구가 증대되고 있다. 이러한 화재 감시 시스템은 화재 상황을 대처할 수 있도록 지원함으로써 피해규모를 축소시킬 수 있다. 그러나 기존 시스템은 일정 주기로 화재 감시를 수행함으로써 화재 판단을 지연시키는 단점이 존재한다. 또한 감시 상황을 확인 할 수 있는 사용자 인터페이스를 제공하지 않는다. 따라서 이러한 두 가지 문제점을 해결하기 위하여 첫째, 조기 위험상황 경보를 위해 새로운 화재 판단 알고리즘(Early Fire Detection Algorithm)을 제안한다. 이는 데이터 분포를 기반으로 하여 화재 판단 시작 주기를 동적으로 설정하기 때문에, 화재 판단 시간 측면에서 기존 알고리즘 보다 우수하다. 둘째, 제안하는 화재 판단 알고리즘을 통하여 사용자 인터페이스를 제공하는 화재 감시 응용 시스템을 개발한다. 마지막으로 성능 실험을 통해, 개발된 시스템이 다양한 화재 상황에서 조기 위험상황 경보를 위해 활용될 수 있음을 보인다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권1호
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• pp.33-37
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• 2002

Insulation aging diagnosis system provides early warning regarding electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear. it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a electromagnetic wave and acoustic signal to diagnose an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, we design of the neuro-fuzzy model that diagnoses an electrical equipment and is investigated in this paper. Validity of the new method is asserted by numerical simulation.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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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.

• 한국방재학회 논문집
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• 제8권6호
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• pp.73-79
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• 2008

경제규모의 증가, 산업화, 도시화 등은 결과적으로 우리국민의 잠재적 지진 위험 증가를 야기하였다. 최근에는 비록 우리나라에서 지진으로 인한 인명과 재산의 손실이 미비했지만, 과거 문헌 기록을 보면 우리나라에서도 대규모 피해를 야기한 지진이 발생한 바 있었으므로, 향후 피해를 유발할 수 있는 지진발생 가능성을 간과할 수는 없다. 현재의 과학기술력으로는 단기 지진 예보가 불가능함을 고려할 때 지진재해 저감을 위하여 취할 수 있는 대비책의 하나로써 지진조기경보체계 확립의 중요성이 점차 증가하고 있다. 지진조기경보체계 확립의 취지는 지진발생 후 강진동이 시작하기 전 수 초 혹은 수십 초의 지진대비시간을 확보하고 미리 계획된 조치를 취함으로써 지진재해를 저감하는 것이다. 본 논문에서는 신속한 지진 발생위치 결정을 위하여 진원 부근 2개의 지진 관측소에서 확보한 초동 도착시간과 주변의 다른 관측소에서는 아직 초동이 관측되지 않았다는 사실을 이용한다. 우리나라 내륙 및 주변해역에서 발생한 주요 지진의 신속한 진앙 위치결정에 이 기술을 적용하였다. 관측소 외부에서 지진이 발생할 경우 이 기술로는 효과적인 지진위치의 결정이 어렵지만, 관측망 내부에서 지진이 발생할 경우 본 기술을 이용하여 지진의 위치를 신속히 결정 할 수 있다. 수도권의 경우 $10{\sim}50$초의 지진대비시간을 확보할 수 있을 것으로 예상되며, 주어진 시간 내에 사전 준비된 조치를 취함으로써 유사시 지진재해저감에 크게 기여할 것이다.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.263-272
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• 2024

A model based on genetic algorithm optimization, GA-SVM, is proposed to warn university students of their status. This model improves the predictive effect of support vector machines. The genetic optimization algorithm is used to train the hyperparameters and adjust the kernel parameters, kernel penalty factor C, and gamma to optimize the support vector machine model, which can rapidly achieve convergence to obtain the optimal solution. The experimental model was trained on open-source datasets and validated through comparisons with random forest, backpropagation neural network, and GA-SVM models. The test results show that the genetic algorithm-optimized radial basis kernel support vector machine model GA-SVM can obtain higher accuracy rates when used for early warning in university learning.

• Smart Structures and Systems
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• 제6권4호
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• pp.405-421
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• 2010

This paper proposes a method for early warning of hazard for pipelines. Many pipelines transport dangerous contents so that any damage incurred might lead to catastrophic consequences. However, most of these damages are usually a result of surrounding third-party activities, mainly the constructions. In order to prevent accidents and disasters, detection of potential hazards from third-party activities is indispensable. This paper focuses on recognizing the running of construction machines because they indicate the activity of the constructions. Acoustic information is applied for the recognition and a novel pipeline monitoring approach is proposed. Principal Component Analysis (PCA) is applied. The obtained Eigenvalues are regarded as the special signature and thus used for building feature vectors. One-class Support Vector Machine (SVM) is used for the classifier. The denoising ability of PCA can make it robust to noise interference, while the powerful classifying ability of SVM can provide good recognition results. Some related issues such as standardization are also studied and discussed. On-site experiments are conducted and results prove the effectiveness of the proposed early warning method. Thus the possible hazards can be prevented and the integrity of pipelines can be ensured.

• The Journal of Asian Finance, Economics and Business
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• 제4권1호
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• pp.39-49
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• 2017

This study develops an early warning system (EWS) to prevent the banking crisis. The proposed system incorporates both the perspective of crises and fundamental characteristics of the banking system in each economy. A fuzzy logic method with data from 1990-2009 is employed to construct the EWS of banking crisis based on 21 pre-determined variables from the aspect of total economy, financial and banking sectors. Our results show: Firstly, South Korea recorded higher probability to have a banking crisis in 1997 as there was large foreign debt in dollars. Secondly, China, Australia and New Zealand banking systems appear to be vulnerable to the crisis in 2007. The surge of China export, FDIs and booming stock market were signs of a heated economy. Australia with high commodity prices was also vulnerable to crisis. Thirdly, Australia, China, Japan and New Zealand banking systems appear to be exposed to the higher chance of a crisis in 2010. Japan with deflation coupled with expensive yen did not augur well for its export. Overall, the findings show that in Asian Financial Crisis 1997/98 and Global Financial Crisis 2008/09, many economies are exposed to a higher probability of having the crisis and this shows an urgent need of having surveillance in these economies.