• Economic and Environmental Geology
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• v.50 no.3
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• pp.195-214
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• 2017

Statistical landslide susceptibility analysis, which is widely used among various landslide susceptibility analysis approaches, predicts the unstable area by analyzing statistical relationship between landslide occurrence locations and landslide controlling factors. However, uncertainties are involved in the procedures of the susceptibility analysis and therefore, fuzzy approach has been used to deal properly with uncertainties. The fuzzy approach used fuzzy set theory and fuzzy membership function to quantify uncertainties involved in landslide controlling factors. Various fuzzy approaches were suggested in the procedure of the membership value determination and fuzzy operation in the previous researches. However, few studies were carried out to compare the analysis results obtained from various approaches for membership function determination and fuzzy operation. Therefore, in this study, the authors selected Jinbu area, which a large number of landslides were occurred at in 2006, to apply two most commonly used methods, the frequency ratio and the cosine amplitude method to derive membership values for each controlling factor. In addition, the integration of different thematic layers to produce landslide susceptibility map was performed by several fuzzy operators such as AND, OR, algebraic product, algebraic sum and Gamma operator. The results of the landslide susceptibility analysis using two different methods for the determination of fuzzy membership values and various fuzzy operators were compared on the basis of ROC graph to check the feasibility of the fuzzy based landslide susceptibility analysis.

• International Journal of Concrete Structures and Materials
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• v.6 no.2
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• pp.111-121
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• 2012

The research presented in this paper analytically examines the fire performance of flat plate buildings. The modeling parameters for the mechanical and thermal properties of materials are calibrated from relevant test data to minimize the uncertainties involved in analysis. The calibrated models are then adopted to perform a nonlinear finite element simulation on a flat plate building subjected to fire. The analysis examines the characteristics of slab deflection, in-plane deformation, membrane force, bending moment redistribution, and slab rotational deformation near the supporting columns. The numerical simulation enables the understanding of structural performance of flat plate under elevated temperature and, more importantly, identifies the high risk of punching failure at slab-column connections that may trigger large-scale failure in flat plate structures.

• Journal of Environmental Science International
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• v.15 no.2
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• Journal of Korean Society for Atmospheric Environment
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• v.5 no.2
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• pp.30-35
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• 1989

To effectively develop and evaluate air pollution control measures, health risk rates due to air pollution must be identified. This article describes the application of a visual analysis and an air pollution-health risk model for determining the impacts of carbon monoxide (CO) exposure on angina pectoris patients in a metropolitan area. The procedures used for analyzing the relationship between CO exposure and the related increase in angina angina attacks for stable angina pectoris patients are described through a case study in the city of Seoul, Korea and the findings show that air-pollution-health risk model and visual analysis can be effective tools for environmental decision-makers, allowing air pollution control scenarios to be developed and evaluated for environmental protection. One of the features of this study is to provide a methodology for translating clinical findings into estimates of the relative contributions of air pollution to all causes of a particular disease. Therefore, there must be appropriate recognition of the uncertainties involved in the study.

• Smart Structures and Systems
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• v.12 no.6
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• pp.641-659
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• 2013

In this paper is studied the influence of the uncertain mass distribution over the floors on the choice of the optimal parameters of a hybrid control system for tall buildings subjected to wind load. In particular, an optimization procedure is developed for the robust design of a hybrid control system that is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The large computational effort inherent in the use of a MC-based procedure is reduced by the employment of the Latin Hypercube Sampling. With reference to a tall building modeled as a multi degrees of freedom system, several numerical analyses are carried out varying the parameters influencing the floors' masses, like the coefficient of variation of the distribution and the correlation between the floors' masses. The procedure allows to obtain optimal designs of the control system that are robust with respect to the uncertainties on the distribution of the dead and live loads.

• Economic and Environmental Geology
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• v.28 no.4
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• pp.433-438
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• 1995

The most popular minimization method is based on the least-squares criterion, which uses the $L_2$ norm to quantify the misfit between observed and synthetic data. The solution of the least-squares problem is the maximum likelihood point of a probability density containing data with Gaussian uncertainties. The distribution of errors in the geophysical data is, however, seldom Gaussian. Using the $L_2$ norm, large and sparsely distributed errors adversely affect the solution, and the estimated model parameters may even be completely unphysical. On the other hand, the least-absolute-deviation optimization, which is based on the $L_1$ norm, has much more robust statistical properties in the presence of noise. The solution of the $L_1$ problem is the maximum likelihood point of a probability density containing data with longer-tailed errors than the Gaussian distribution. Thus, the $L_1$ norm gives more reliable estimates when a small number of large errors contaminate the data. The effect of outliers is further reduced by M-fitting method with Cauchy error criterion, which can be performed by iteratively reweighted least-squares method.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.316-319
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• 2005

Contaminated area should be identified for designing polluted groundwater cleanup plan. A methodology was suggested to identify a contaminant plume distribution geostatistically. James & Gorelick (1994) suggested a methodology to evaluate data worth as expected reducing remediation cost. In this study, their methodology was modified to evaluate data worth as expected reducing uncertainty of the contaminant plume distribution. In suggested methodology, the source identification model by Mahar & Datta (2001) using a forward solute transport model is integrated. Suggested methodology was assessed by two simple example problems and its result represented reducing uncertainties of contaminant plume distribution successfully.

• Journal of Animal Environmental Science
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• v.13 no.1
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• pp.1-12
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• 2007

Stored animal manure is considered as a significant agricultural source of methane $(CH_4)$ and nitrous oxide $(N_2O)$ which have 23 and 297 times higher global warming effect when compared to carbon dioxide $(CO_2)$. Uncertainties caused by lack of understanding physical and biochemical environment in stored animal manure and by errors of emission measurement methods, even though many researches measuring $CH_4\;and\;N_2O$ emissions from stored manure have been conducted for a few decades. In this paper, general information of $CH_4\;and\;N_2O$ generation and emissions from stored animal manure and the measurement methods for quantifying $CH_4\;and\;N_2O$ emissions are discussed.

• Environmental Analysis Health and Toxicology
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• v.18 no.3
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• pp.183-191
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• 2003

Although the variety and quantities of chemicals used have been increasing, no management strategies have been developed for these chemicals in our country. Therefore, it is important to identify the hazardous characteristics of chemicals and establish reasonable and effective management plans for them. However, because insufficient resources are available to evaluate all aspects of many varieties of chemicals, studies on suitable chemical ranking and scoring (CRS) system should be performed to ensure effective screening of priority chemicals.. In addition, because most CRS systems have their own goals, it is impossible for only one generic system to be consistent with all the uses that have been developed. Therefore, priority systems should be developed with specific and clearly defined purposes in our nation. In this study, we investigated and discussed exist-ing CRS systems, and proposed several elements and principles when designing CRS systems. First of all, the system should have clearly defined goals, keep neutral, and employ simple methods. In addition, researchers need to perform sensitivity analysis to find the main variables responsible for uncertainties and use the tiered approach to compose the effective management strategies for chemicals.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.159-168
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• 2013

The effect of structural uncertainties or measurement errors on damage detection results makes the robustness become one of the most important features during identification. Due to the wide use of vibration signatures on damage detection, the development of vibration-based techniques has attracted a great interest. In this work, a review on vibration-based robust detection techniques is presented, in which the robustness is considerably improved through modeling error compensation, environmental variation reduction, denoising, or proper sensing system design. It is hoped that this study can give help on structural health monitoring or damage mitigation control.