Due to the discontinuous nature of uncertainty quantification in conventional evidence theory(ET), the computational cost of reliability analysis based on ET model is very high. A novel ET model based on fuzzy distribution and the corresponding combination rule to synthesize the judgments of experts are put forward in this paper. The intersection and union of membership functions are defined as belief and plausible membership function respectively, and the Murfhy's average combination rule is adopted to combine the basic probability assignment for focal elements. Then the combined membership functions are transformed to the equivalent probability density function by a normalizing factor. Finally, a reliability analysis procedure for structures with the mixture of epistemic and aleatory uncertainties is presented, in which the equivalent normalization method is adopted to solve the upper and lower bound of reliability. The effectiveness of the procedure is demonstrated by a numerical example and an engineering example. The results also show that the reliability interval calculated by the suggested method is almost identical to that solved by conventional method. Moreover, the results indicate that the computational cost of the suggested procedure is much less than that of conventional method. The suggested ET model provides a new way to flexibly represent epistemic uncertainty, and provides an efficiency method to estimate the reliability of structures with the mixture of epistemic and aleatory uncertainties.
KSCE Journal of Civil and Environmental Engineering Research
/
v.35
no.1
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pp.173-185
/
2015
This study aims to investigate the characteristics and types of car accidents and establish a prediction model by analyzing 456 car accidents having occurred in the 11 tunnels in Busan, through statistical analysis techniques. The results of this study can be summarized as below. As a result of analyzing the characteristics of car accidents, it was found that 64.9% of all the car accidents took place in the tunnels between 08:00 and 18:00, which was higher than 45.8 to 46.1% of the car accidents in common roads. As a result of analyzing the types of car accidents, the car-to-car accident type was the majority, and the sole-car accident type in the tunnels was relatively high, compared to that in common roads. Besides, people at the age between 21 and 40 were most involved in car accidents, and in the vehicle type of the first party to car accidents, trucks showed a high proportion, and in the cloud cover, rainy days or cloudy days showed a high proportion unlike clear days. As a result of analyzing the principal components of car accident influence factors, it was found that the first principal components were road, tunnel structure and traffic flow-related factors, the second principal components lighting facility and road structure-related factors, the third principal factors stand-by and lighting facility-related factors, the fourth principal components human and time series-related factors, the fifth principal components human-related factors, the sixth principal components vehicle and traffic flow-related factors, and the seventh principal components meteorological factors. As a result of classifying car accident spots, there were 5 optimized groups classified, and as a result of analyzing each group based on Quantification Theory Type I, it was found that the first group showed low explanation power for the prediction model, while the fourth group showed a middle explanation power and the second, third and fifth groups showed high explanation power for the prediction model. Out of all the items(principal components) over 0.2(a weak correlation) in the partial correlation coefficient absolute value of the prediction model, this study analyzed variables including road environment variables. As a result, main examination items were summarized as proper traffic flow processing, cross-section composition(the width of a road), tunnel structure(the length of a tunnel), the lineal of a road, ventilation facilities and lighting facilities.
According as the quality of life is improved along with economic growth, in the road plan and design sector also, it is now progressed that function oriented design is changed into the landscape oriented design that considers eyesight and emotion, which are psychological properties of users. Accordingly this study tries to come up with reasonable and objective methods to extract various emotional adjectives, which were found by the survey, while minimizing difference among characteristics of emotion and cognition of individuals. First, given semantic differential, based on various emotional adjectives that were found through the survey with the scale up to five points, the author extracted representative emotional adjectives through an element analysis, which is a conventional method of the previous research, and through an identification analysis which is suggested by this study, and then established model I of Quantification. And by using the established quantification model, the author presumed satisfaction degree, and through verifying pair wise comparison with actual satisfaction degree, the author found the results from identification and correlation analysis methods are most similar to actual satisfaction degree. As a result, the author could check the above emotional and correlation analyses were appropriate methods for comprehending which emotional elements are applicable when a continuous road landscape is designed by identification and correlation analyses.
With respect to the trend of highway traffic accident, highway accident is in decline, whileas, the fatality is on an increasing trend. Thus, many efforts to decrease highway traffic accidents and improve the safety, are required. In particular, in case of highway, the management standard by grade for accident black spot is designated. Thus, investing the effect factors by grade for highway traffic accident is required in detail. Thus, in this study, the factors affecting the traffic accidents among the environmental factors based on the graded data for the accident black spot in the applicable section targeting the Seoul-Pusan Express Highway, were reviewed; accident forecasting model which would analyze the characteristics of the accidents for determining the accident grade, was developed. As a result of establishing a model by using Quantification Theory of Type II, considering the characteristics of the dependent and independent variables based on the geometric structure, 'the fixed variable' among the variables relating to the accident, for the variables influencing over the accident grade, 'the type of vans, a chassis and people', 'the trailers, special vehicles and chassis people' and 'the negligence of watching and cloudy weather' were analyzed as common factors, in case of 'horizontal alignment', 'longitudinal slope' and, 'barricade' respectively.
In this study, damages due to the aircraft noise were examined in more than 190 elementary, middle and high schools near the airports in Korea, and the persecutory idea forecast model was established using the quantification theory type II. Via the survey of 1,012 teachers in the schools, a class interference forecast model was established, and the noise characteristics of five areas, four military/civil common-use airports and one shooting range, were examined. The following conclusions were made from the study. WECPNL values in the five military/civil common-use airports showed that all of them were Class 1 or 2 affected areas, which indicated that they had serious aircraft noise problems to be addressed. The most influential factor in the aircraft noise persecutory idea model was the distance between the airport and the school. It showed a positive relationship at a distance of less than 5 km, and a negative relationship at a distance of 10 km or more. The number and time of aircraft noise exposure as well as the types of airports and window structures had strong influences. The forecast model had a correlation ratio of 0.56, which indicates that it is highly appropriate. In the class interference factor analysis, the time and number of aircraft noise exposure were strong influential factors, and the results varied according to the service duration and sex of teachers. This model had a correlation ratio of 0.61, which indicates it is highly appropriate.
In this paper, we propose a novel method to analyze and quantitatively evaluate the impression of landscapes and soundscapes about traditional area of Chungnam Asan city in Korea. For this, we collated data about impression evaluation of Korean and Japanese students and, based on these result, we proved the validity and usefulness of the evaluation system that we proposed through this study. The research process conducted in this study as follows: first of all, we had selected five traditional places of interest in Asan City, and investigated various conditional elements of the area including soundscapes which is forming the landscape using video camera. And we made both Korean and Japanese students evaluate the impression for these videotaped landscape data through using the SD(semantic differential) method. And then, we quantified these qualitative data through applying the quantification theory and cluster analysis method to them. Though this process, we could obtain both data as a result derived by classifying each sample and categorizing levels of those impression evaluation. Because of totally difference between those two analyzing processes, which one is for sample classification and the other is for determining impression level, we could validate the usefulness of our evaluation system through conducting comparative analysis of results from both methods. Analysis showed that our novel evaluation system for landscape is effective and, in most part of the traditional landscape, Japanese students' responses are different far from the Korean students' responses.
This study was carried out to analyze the characteristics of each factors by using the quantification theory(I) for prediction of landslide hazard area. The results obtained from this study were summarized as follows; The stepwise regression analysis between landslide sediment ($m^3$ ) and environmental factors, factors affecting landslide sediment ($m^3$ ) were high in order of mixed (forest type), < 15 cm(soil depth), 801~1,200 m (altitude), $31{\sim}40^{\circ}$ (slope gradient), 46 cm < (soil depth), 1,201 m < (altitude) and s(aspect). According to the range, it was shown in order of soil depth (0.3784), altitude (0.2876), forest type (0.2409), slope gradient (0.1728) and aspect (0.1681). The prediction of landslide hazard area was estimated by score table of each category. The extent of prediction score was 0 to 1.2478, and middle score was 0.6239. Class I was over 1.1720, class II was 0.7543 to 0.1719, class III was 0.4989 to 0.7542 and class IV was below 0.4988.
Park, Joon-Hyung;Jung, Su-Young;Lee, Kwang-Soo;Lee, Ho-Sang
Journal of Korean Society of Forest Science
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v.108
no.4
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pp.513-521
/
2019
With rapid climate change and increasing global warming, the distribution of evergreen broad-leaved trees (EBLTs) is gradually expanding to the inland regions of Korea. The aim of the present study was to analyze the survival rate of 148 EBLT plantations measuring 180 ha and to determine the optimal plantation size that would help in coping with climate change in the warm, temperate climate zone of the Korean peninsula. For enhancing the reliability of our estimated survival model, we selected a set of 11 control variables that may have also influenced the survival rates of the EBLTs in the 148 plantations. The results of partial correlation analysis showed that the survival rate of 67.0±26.9 of the EBLTs in the initial plantation year was primarily correlated with plantation type by the crown closure of the upper story of the forest, wind exposure, and precipitation. For predicting the probability of survival by quantification theory, 148 plots were surveyed and analyzed with 11 environmental site factors. Survival rate was in the order of plantation type by the crown closure of upper story of the forest, wind exposure, total cumulative precipitation for two weeks prior to planting, and slope stiffness in the descending order of score range in the estimated survival model for the EBLTs with the fact that survival rate increased with shade rate of upper story to some extent.
Lee, Sung-Jae;Kim, Gil Won;Jeong, Won-Ok;Kang, Won-Seok;Lee, Eun-Jai
Journal of Korean Society of Forest Science
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v.110
no.1
/
pp.64-71
/
2021
Recently, climate change has gradually accelerated the occurrence of landslides. Among the various effects caused by landslides,debris flow is recognized as particularly threatening because of its high speed and propagating distance. In this study, the impacts of various factors were analyzed using quantification theory(I) for the prediction of debris flow hazard soil volume in Seoraksan National Park, Korea. According to the range using the stepwise regression analysis, the order of impact factors was as follows: vertical slope (0.9676), cross slope (0.6876), altitude (0.2356), slope gradient (0.1590), and aspect (0.1364). The extent of the normalized score using the five-factor categories was 0 to 2.1864, with the median score being 1.0932. The prediction criteria for debris flow occurrence based on the normalized score were divided into four grades: class I, >1.6399; class II, 1.0932-1.6398; class III, 0.5466-1.0931; and class IV, <0.5465. Predictions of debris flow occurrence appeared to be relatively accurate (86.3%) for classes I and II. Therefore, the prediction criteria for debris flow will be useful for judging the dangerousness of slopes.
Proceedings of the Korean Society for Rock Mechanics Conference
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2000.09a
/
pp.171-181
/
2000
Many Studies of tunnel and tunnelling safety have been developed continuously based on the increasing social interests in underground space since 1990's in Korea. Because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities, underground facilities have been created as a great extent in view of less land space available. In this study, a lot of types of tunnel failure were surveyed and the detail causes were studied after many cases of tunnel failure were collected. There were suggested brief countermeasure of tunnel failure through case study. An expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.
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