• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.101-112
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• 2018

A lot of manpower and budgets are being used to prevent fires, and only a small portion of the data generated during this process is used for disaster prevention activities. This study develops a prediction model of fire occurrence probability based on data mining in order to more actively use these data for disaster prevention activities. For this purpose, variables for predicting fire occurrence probability of various buildings were selected and data of construction administrative system, national fire information system, and Korea Fire Insurance Association were collected and integrated data set was constructed. After appropriate data cleansing and preprocessing, various data mining methodologies such as artificial neural network, decision trees, SVM, and Naive Bayesian were used to develop a prediction model of the fire occurrence probability of buildings. The most accurate model among the derived models is Linear SVM model which shows 68.42% as experimental data and 63.54% as verification data and it is the best model to predict fire occurrence probability of buildings. As this study develops the prediction model which uses only the set values of the specific ranges, future studies may explore more opportunites to use various setting values not shown in this study.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.3
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• pp.135-145
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• 2020

Recently, the disaster rate of the construction industry has increased with high-rise, and complexity of the building, unlike the decrease in the disaster rate in other industries. Although risk assessment is performed to reduce the occurrence of disasters, it is difficult to estimate the risks accurately due to activity in which no disaster has occurred, and inconsistencies in the level of details of work. In this study, in order to evaluate the risk of the major activity for the apartment construction work, the activity was identified by referring to the risk assessment model of construction industry type by the KOSHA. The construction work types and activities were consistently organized in level of work into nine work types and 82 activities were through experts consultation. Analyzing the disaster types that occurred during work through KOSHA disaster cases, calculating the probability of disaster occurrence according to the type of disaster, and combining the probability of disaster with the severity of disaster to estimate the risk assessment method was presented. Using the daily report of the construction site of the apartment, the results of a case study confirmed the validity of the risk calculation method presented in this study.

• Journal of Information Technology Applications and Management
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• v.15 no.2
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• pp.67-82
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• 2008

Risk that breed large size disaster is happening variously for cause at social. natural a management. Incidence and damage scale are trend that increase rapidly than past. In these circumstance, to keep operational continuity of organization, area, society, risk management action that establish systematic counter measure estimating and analyze occurrence possibility and expectation damage of risk is essential indispensable issue and the best countermeasure. Risk management action does by main purpose establish optimum disaster reduction countermeasure. To deduce various countermeasure, process that estimate and analyze occurrence possibility and expectation damage of risk is essential indispensable issue. Therefore, this paper studies process design that can presume risk occurrence frequency and damage scale through distribution of probability.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.1-6
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• 2012

To achieve the forest fire management goals such as early detection and quick suppression, fire resources should be allocated at high probability area where forest fires occur. The objective of this study was to develop and validate models to estimate spatially distributed probabilities of occurrence of forest fire. The models were builded by exploring relationships between fire ignition location and forest, terrain and anthropogenic factors using logistic regression. Distance to forest, cemetery, fire history, forest type, elevation, slope were chosen as the significant factors to the model. The model constructed had a good fit and classification accuracy of the model was 63%. This model and map can support the allocation optimization of forest fire resources and increase effectiveness in fire prevention and planning.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.373-383
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• 2006

The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.11-21
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• 2001

Domestic construction industry has considerable level of construction performance and technology thanks to the economic development and as the result of performing diverse oversea construction project. However, construction disasters have been steadily increasing, and do severe disasters at faster pace. Most of such disasters happen at small and small medium-sized construction fields, which contract size is less than 10 billion won. small and medium-sized construction fields are not obliged to designate a safety manager, and have limitations in engaging self-regulating disaster prevention activities due to reduced budget for safety facilities. For the small and medium-sized construction sites with less than 10 billion won, the Ministry of Labor has been carrying out mobile inspections of construction safety. However, the effect so far is insignificant and an improvement plan is required. Therefore, in the present thesis, we derive problems appearing in the current construction safety mobile inspection system, investigate and study systems in foreign countries, and suggest an efficient and effective plan to operate safety technology inspections. First of all, we establish a standard to select sites to be inspected that are high in construction risk and disaster occurrence probability In addition, we suggest a plan to take administrative and judiciary measures based on the total score for disaster factors considering the disaster occurrence probability and the illegal practices. Furthermore, a scheme to maximize the effect of disaster prevention is sought by building an organic cooperative system between the Ministry of Labor, Korea Occupational Safety ＆ Health Agency and other organizations specialized in instruction of construction disaster prevention. Finally, we induce a research conclusion that leads to self-regulating safety management through checking and instructing systematic management on mobile inspections.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.69-78
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• 2010

Haines index which include the rating of atmosphere instability and dryness indicated the potential of the forest fire danger. In this study, the relationships between forest fire occurrence and Haines index were analyzed. The probability of forest fire occurrence was the highest in April and HI 5, 6 and the dryness of atmosphere was higher than the atmosphere instability. Therefore, It was proved that HI affected on the forest fire occurrence and propagation.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.126-135
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• 2011

In this study, the algorithm for priority area of forest fire surveillance was developed to enhance the effectiveness of fire detection. The high priority surveillance area for forest fire detection was defined as the area with not only low value of viewshed analysis of the lookouts and detection cameras but also high fire occurrence probability. To build the priority map, fuzzy function and map algebra were used. The analysis results of Bonghwa-gun, Gyeongbuk Province, showed that the surveillance priority of central and southern area is higher than north area. This algorithm could be used in the allocation of fire prevention resources and selection of suitable point for new fire detection system.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.163-171
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• 2010

Forest fires have potentials to change the structure and function of forest ecosystems and significantly influence on atmosphere and biogeochemical cycles. Forest fire also affects the quality of public benefits such as carbon sequestration, soil fertility, grazing value, biodiversity, or tourism. The prediction of fire occurrence and its spread is critical to the forest managers for allocating resources and developing the forest fire danger rating system. Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behaviors and its spread. Thus, meteorological factors as well as social factors were considered in the fire danger rating systems. A total of 298 forest fires occurred during the fall season from 2002 to 2006 in South Korea were considered for developing a logistic model of forest fire occurrence. The results of statistical analysis show that only effective humidity and temperature significantly affected the logistic models (p<0.05). The results of ROC curve analysis showed that the probability of randomly selected fires ranges from 0.739 to 0.876, which represent a relatively high accuracy of the developed model. These findings would be necessary for the policy makers in South Korea for the prevention of forest fires.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.133-134
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• 2022

Recently, the criteria for assessing industrial accidents have been replaced by the mortality rate. It was found that the number of deaths from excavation work was the highest among construction machinery. The risk assessment is being conducted, however the industrial accident mortality rate has not decreased. Accordingly, this study aims to provide the basic for the create of a risk assessment model specialized in construction work at excavator. It provides absolute value from the risk model which is capable of delivery the probability of a disaster. In addition, we provide a relative risk model that compares the risk through scores between detailed works. The relative risk model is combined by likelihood and severity; the likelihood indicates the frequency of accidents and the severity indicates seriousness of fatal accidents. A variable that reflects the conditions of the construction site was added to the risk assessment model based on past disaster cases. And using the concepts of probability and average, the risk assessment process was quantified and used as an objective indicator. Therefore, the model is expected to reduce disasters by raising the awareness of disasters.