• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.351-361
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• 2021

The seriousness of fire is rising because fire causes enormous damage to property and human life. Therefore, this study aims to predict various risk factors affecting fire by fire type. The predictive analysis of fire factors was carried out targeting Gyeonggi-do, which has the highest number of fires in the country. For the analysis, using machine learning methods SVM (Support Vector Machine), RF (Random Forest), GBRT (Gradient Boosted Regression Tree) the accuracy of each model was presented with a high fit model through MAE (Mean Absolute Error) and RMSE (Root Mean Squared Error), and based on this, predictive analysis of fire factors in Gyeonggi-do was conducted. In addition, using machine learning methods such as SVM (Support Vector Machine), RF (Random Forest), and GBRT (Gradient Boosted Regression Tree), the accuracy of each model was presented with a high-fit model through MAE and RMSE. Predictive analysis of occurrence factors was achieved. Based on this, as a result of comparative analysis of three machine learning methods, the RF method showed a MAE = 1.765 and RMSE = 1.876, as well as the MAE and RMSE verification and test data were very similar with a difference between MAE = 0.046 and RMSE = 0.04 showing the best predictive results. The results of this study are expected to be used as useful data for fire safety management allowing decision makers to identify the sequence of dangers related to the factors affecting the occurrence of fire.

• The Journal of Bigdata
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• v.6 no.1
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• pp.133-144
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• 2021

This paper derives the fire risk of buildings in Seoul through the prediction of property damage and the occurrence of fires. This study differs from prior research in that it utilizes variables that include not only a building's characteristics but also its affiliated administrative area as well as the accessibility of nearby fire-fighting facilities. We use Ensemble Voting techniques to merge different machine learning algorithms to predict property damage and fire occurrence, and to extract feature importance to produce fire risk. Fire risk prediction was made on 300 buildings in Seoul utilizing the established model, and it has been derived that with buildings at Level 1 for fire risks, there were a high number of households occupying the building, and the buildings had many factors that could contribute to increasing the size of the fire, including the lack of nearby fire-fighting facilities as well as the far location of the 119 Safety Center. On the other hand, in the case of Level 5 buildings, the number of buildings and businesses is large, but the 119 Safety Center in charge are located closest to the building, which can properly respond to fire.

• Fire Science and Engineering
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• v.23 no.4
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• pp.91-97
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• 2009

When the fire occur in a special place as High-rise building, find the solution from minimize the potential risk factors that caused to develop the human and materials damage by analysis. Through preventive activities are suppression of the fire occurrence or prevent the fire and extinguish the fire early. However, introduction of scientific suppression program could predict in advance the progress of the fire, or to block the path by using Intel Regent or Fire grid.

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.257-264
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• 1991

Korea has accomplished the afforestation of its forest land in the early 1980's. To meet the increasing demand for forest products and forest recreation, a development of scientific forest management system is needed as a whole. For this purpose the development of efficient forestfire management system is essential. In this context, the purpose of this study is to develop a theoretical foundation of forestfire danger rating system. In this study, it is hypothesized that the degree of forestfire risk is affected by Weather Factor and Man-Caused Risk Factor. (1) To accommodate the Weather Factor, a statistical model was estimated in which weather variables such as humidity, temperature, precipitation, wind velocity, duration of sunshine were included as independent variables and the probability of forestfire occurrence as dependent variable. (2) To account man-caused risk, historical data of forestfire occurrence was investigated. The contribution of man's activities make to risk was evaluated from three inputs. The first, potential risk class is a semipermanent number which ranks the man-caused fire potential of the individual protection unit relative to that of the other protection units. The second, the risk sources ratio, is that portion of the potential man-caused fire problem which can be charged to a specific cause. The third, daily activity level is that the fire control officer's estimate of how active each of these sources is, For each risk sources, evaluate its daily activity level ; the resulting number is the partial risk factor. Sum up the partial risk factors, one for each source, to get the unnormalized Man-Caused Risk. To make up the Man-Caused Risk, the partial risk factor and the unit's potential risk class were considered together. (3) At last, Fire occurrence index was formed fire danger rating estimation by the Weather Factors and the Man-Caused Risk Index were integrated to form the final Fire Occurrence Index.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2011.04a
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• pp.67-72
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• 2011

본 연구는 건축물 화재성상 시뮬레이션 개발을 위한 기초 연구 자료로서 건축물 화재시 높은 비중의 가연물과 좁은 이격거리로 인하여 화재 발생시 급격히 연소확대될 위험성이 높고, 개구분출화염이 건물 화재확산의 중요한 요인이나 이 분야에 대한 연구는 부족한 실정이며, 또한 화재성상 예측시 기존 시뮬레이션에서 화재확산의 중요한 인자인 바람의 요소가 고려되지 않았다. 이에 대하여 개구분출 실물화재실험을 통하여 유풍시 개구분출화염에 기인한 수식을 도출하였으며, 이를 기반으로 향후 기존의 바람 인자를 고려하지 않은 화재성상 예측 시뮬레이션에 적용 가능성을 모색하여 국내 실정에 맞는 화재 성상 시뮬레이션 개발 구축에 대한 기초자료로 제시한다.

• Journal of Navigation and Port Research
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• v.42 no.4
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• pp.283-290
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• 2018

Due to the environmental factors of the sea, ship accidents always contain an inclination angle. The change in the ship affects not only the evacuation speed of passengers but also the fire growth in the ship. For this reason, when analyzing the fire, it is necessary to analyze the risks by considering conditions of inclination. In this study, the temperature that affects the fire was calculated by alteration of ship's heel and trim angle and analyzed using FLUENT. Based on fire occurrence position, evacuation should be done within 37 seconds under the condition of $-10^{\circ}$ heeling angle and 36 seconds under the condition of $-10^{\circ}$ trim angle. However, it was predicted that the evacuation will not be affected under the conditions of $+10^{\circ}$ heel angle and $+10^{\circ}$ trim angle. For these reasons, it is confirmed that when the ship is on fire, evacuation measures should be considered based on the heel and trim conditions as per the location of the fire.

• Spatial Information Research
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• v.22 no.3
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• pp.71-77
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• 2014

There are numbers of unpredictable risk factors in the disaster scenes such as fire, explosion and fail to early life-saving or holding the flames which can lead to massive damage. In particular, fire-fighters who arrive on the scene within 5 minutes after dispatching, have a limitation to get aware to the situation of scene fully, because of immediate deploy to disaster scene with limited information. This situation may lead to disturbance that fire-fighters perform effective fire-fighting activities, to put fire-fighter's life at risk by misjudge the situation. Previous domestic and International studies focused vulnerability for spatial area or features which can damage to life and property in the event of anticipated. In this study, we have been developed fire-fighting vulnerable zone model that can analyze comprehensively hindrance factors for fire-fighting activities targeting whole life cycle of fire-fighting activities from dispatch to fire suppression or life-saving. In addition, we have been given shape to finality and applicability for our model by defining the new concept of fire-fighting vulnerable zone which can be distinguished from the concept of fire vulnerable area in previous studies. The results of this study can be used to analysis fire-fighting vulnerable zone type analysis, establish fire-fighting policies and improve the performance of decision-making process.

• Fire Science and Engineering
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• v.18 no.1
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• pp.54-66
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• 2004

In this article, we are to suggest the hazard-assessing method for the underground pipelines, and find out the pipeline-maintenance schemes of high efficiency in cost. Three kinds of methods are applied in order to refer to the approaching methods of listing the hazards for the underground pipelines: the first is RBI(Risk Based Inspection), which firstly assess the effect of the neighboring population, the dimension, thickness of pipe, and working time. It enables us to estimate quantitatively the risk exposure. The second is the scoring system which is based on the environmental factors of the buried pipelines. Last we quantify the frequency of the releases using the present THOMAS' theory. In this work, as a result of assessing the hazard of it using SPC scheme, the hazard score related to how the gas pipelines erodes indicate the numbers from 30 to 70, which means that the assessing criteria define well the relative hazards of actual pipelines. Therefore. even if one pipeline region is relatively low score, it can have the high frequency of leakage due to its longer length. The acceptable limit of the release frequency of pipeline shows 2.50E-2 to 1.00E-l/yr, from which we must take the appropriate actions to have the consequence to be less than the acceptable region. The prediction of total frequency using regression analysis shows the limit operating time of pipeline is the range of 11 to 13 years, which is well consistent with that of the actual pipeline. Concludingly, the hazard-listing scheme suggested in this research will be very effectively applied to maintaining the underground pipelines.