• Steel and Composite Structures
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• 제49권4호
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• pp.407-417
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• 2023

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• 한국환경보건학회지
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• 제42권5호
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• pp.302-313
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• 2016

Objectives: This study was conducted to assess environmental health status on a local scale using environmental health-related indicators. It demonstrated the possibility of using a structural equation model, a methodological approach to provide synthesized information. Methods: Eighteen indicators were selected from official statistical data published by local governments. Each environmental health-related indicator was classified according to the PSR (pressure-state-response) model. Aggregation methods were performed using principal component analysis and fuzzy sets. Results: The five principal components were classified through principal component analysis (PCA) and obtained eigenvalues >1.0 from the initial 18 indicators. The aggregated index was obtained by condensing the original information into two broad and simple categories through fuzzy sets. Conclusion: This could be useful in that the aggregation procedure may provide a basis for establishing environmental health policies and a decision-making process. However, the availability and quality of indicators, assessment of aggregation method bias, choice of weighted scores for indicators, and other factors should be examined in future studies.

• Geomechanics and Engineering
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• 제23권5호
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• pp.441-454
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• 2020

The tunnel collapse, large deformation of surrounding rock, water and mud inrush are the major geological disasters in soft rock tunnel construction. Among them, tunnel collapse has the most serious impact on tunnel construction. Current research backed theories have certain limitations in identifying the collapse risk of soft rock tunnels. Examining the Zhengwan high-speed railway tunnel, eight soft rock tunnel collapse influencing factors were selected, and the combination of indicator weights based on the analytic hierarchy process and entropy weighting methods was obtained. The results show that the groundwater condition and the integrity of the rock mass are the main influencing factors leading to a soft rock tunnel collapse. A comprehensive fuzzy evaluation model for the collapse risk of soft rock tunnels is being proposed, and the real-time collapse risk assessment of the Zhengwan tunnel is being carried out. The results obtained via the fuzzy evaluation model agree well with the actual situation. A tunnel section evaluated to have an extremely high collapse risk and experienced a local collapse during excavation, verifying the feasibility of the collapse risk evaluation model. The collapse risk evaluation model proposed in this paper has been demonstrated to be a promising and innovative method for the evaluation of the collapse risk of soft rock tunnels, leading to safer construction.

• 한국지능시스템학회논문지
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• 제27권2호
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• pp.113-118
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• 2017

선박 충돌 사고를 예방하기 위해 충돌위험도를 미리 추정하여 알려주는 다양한 연구들이 꾸준히 소개되고 있고, 일부 항해장비에 적용되고 있다. 하지만, 충돌위험을 미리 알려주었을 때, 실제 운항자는 충분히 피항 가능한 상황인데 위험성을 알린다고 판단하여 위험 경고를 무시하거나 장비의 알람 기능을 꺼놓는 경우도 많은 것으로 알려져 있다. 선박 충돌 위험 예측이 운항자들에게 좀 더 유용해지기 위해서는 실제 선박들의 습관화된 충돌 회피 동작을 고려할 필요가 있다. 이 연구는 선박에서의 충돌 회피 조치가 어떻게 이루어지고 있는지 조우 유형별로 분석하고 이력을 관리하기 위한 시스템을 제안한다. 특히, 충돌회피를 위한 초기대응에 대한 적절성을 판단하는 핵심 모듈을 뉴로-퍼지 기반 추론 형태로 상세히 설계하고 테스트함으로써 제안하는 시스템의 타당성을 보인다.

• Geomechanics and Engineering
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• 제24권5호
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• pp.407-418
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• 2021

Due to the complexity of the causes of the sliding mass instabilities, landslide susceptibility and hazard evaluation are difficult, but they can be more carefully considered and regionally evaluated by using new programming technologies to minimize the hazard. This study aims to evaluate the landslide hazard zonation in the Tabriz region, Iran. A fuzzy logic-based multi-criteria decision-making method was proposed for susceptibility analysis and preparing the hazard zonation maps implemented in MATLAB programming language and Geographic Information System (GIS) environment. In this study, five main factors have been identified as triggering including climate (i.e., precipitation, temperature), geomorphology (i.e., slope gradient, slope aspect, land cover), tectonic and seismic parameters (i.e., tectonic lineament congestion, distribution of earthquakes, the unsafe radius of main faults, seismicity), geological and hydrological conditions (i.e., drainage patterns, hydraulic gradient, groundwater table depth, weathered geo-materials), and human activities (i.e., distance to roads, distance to the municipal areas) in the study area. The results of analyses are presented as a landslide hazard map which is classified into 5 different sensitive categories (i.e., insignificant to very high potential). Then, landslide susceptibility maps were prepared for the Tabriz region, which is categorized in a high-sensitive area located in the northern parts of the area. Based on these maps, the Bozgoosh-Sahand mountainous belt, Misho-Miro Mountains and western highlands of Jolfa have been delineated as risk-able zones.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.

• 한국항만경제학회지
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• 제28권3호
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• pp.27-44
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• 2012

세계 각국은 신재생 에너지 가운데 해상풍력 발전에 국가적 역량을 집중하면서 해상풍력 터빈의 용량을 대형화하고 있다. 특히 해상풍력 터빈은 부피와 중량이 큰 특징이 있어 육상운송에 어려움이 있어 해상풍력 전용항만이 필요하다. 따라서 본 연구에서는 국내 해상풍력 단지가 성공적으로 조성 및 운영될 수 있도록 최적의 전용항만 입지선정에 영향을 끼치는 평가항목을 분석하여 국가정책 의사결정에 올바른 방향을 제시하고자 하였다. 이를 위해 Fuzzy-AHP 기법을 적용하여 평가항목 별 중요도를 도출하였다. 평가항목은 수준 I에서는 5가지, 즉 집적 요인, 지역 요인, 경제 요인, 입지 요인, 컨소시엄 요인이 선정되었다. 이 가운데 집적 요인 37.4%, 입지 요인 34.2%, 경제 요인 24.5%가 주요한 항목으로 분석되었다. 그리고 수준 II에서는 각 요인에 3가지 항목이 선정되어 모두 15개 평가항목이 선정되었다. 분석 결과를 보면, 해상풍력 전용항만 입지 선정에 있어서 핵심적으로 고려되어야 할 항목은 풍력산업의 집적도, 항만운영의 경제성을 확보하는 물동량 규모, 해상풍력 관련 산업의 발달 정도, 그리고 개발될 해상풍력 단지와의 근접성으로 나타났다. 즉 해상풍력 전용항만 건설은 항만건설 측면과 해상풍력 터빈 제조기업의 입지 선호지역을 복합적으로 고려해야 한다는 의미이다. 따라서 정부가 해상풍력 전용항만을 건설함에 있어서 풍력터빈 제조기업의 의견을 충분히 반영하는 것이 요구된다.

• 한국농림기상학회지
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• 제26권1호
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• pp.75-88
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• 2024

우리나라는 수요 곡물의 대부분을 수입으로 의존하기 때문에 주요 곡물 수출 국가의 재배 면적과 생산량 예측을 통해 식량안보를 증진시킬 수 있다. 특히, 밀 주요 수출국인 우크라이나를 대상으로 재배지역의 변화 전망을 파악하는 것이 장기적인 밀 수급에 대한 미래 정책 결정에 도움을 줄 수 있다. 본 연구에서는 작물의 기후적합도를 예측하는 Fuzzy Union 모델을 사용하여 과거 기후조건(1970~2000)에서 우크라이나 지역의 밀의 기후적합도를 평가하고자 하였다. 우크라이나 통계청으로부터 밀 생산량과 재배면적 통계자료를 수집하였다. 또한, 위성영상을 활용하여 작물의 재배면적과 수량에 대한 공간자료인 EarthStat 자료를 수집하였다. 모델로 계산된 기후적합도와 밀 관측지점과 비교하여 임계값을 설정하였다. EarthStat 자료와 실제 관측자료를 비교한 결과 일정 지역에서 재배면적과 수량이 일치하지 않는 지역들이 존재하였다. 과거 기후 조건에서 산출된 기후적합도의 경우에도 지역적인 차이를 보였다. 예를 들어, 우크라이나의 서북부 지역에서 0.8 이상의 높은 기후적합도의 분포를 보였으나 동남부 지역에서는 0.15 수준의 낮은 기후적합도를 보였다. 그러나, 기후적합도의 행정구역별 통계량과 실제 밀 재배면적과 생산량을 비교한 결과 일정 수준의 상관관계를 가졌다. 특히, 단위면적당 생산량과 기후적합도의 상관계수는 0.647로 중위 정상관을 나타냈다. 이러한 결과는 기후적합도를 활용하여 재배면적 추정 및 단위면적당 수량 예측이 가능함을 시사하였다.

• Industrial Engineering and Management Systems
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• 제11권1호
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• pp.54-69
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• 2012

Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.

• Journal of Radiation Protection and Research
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• 제26권1호
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• pp.19-26
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• 2001

사고시 대기확산을 평가하기 위해서 USNRC Reg. Guide 1.145에 기초하여 개발된 PAVAN과 XOQAR 코드는 X/Q 값을 계산할 때, 누적빈도에 대하여 X/Q 값이 log-normal 용지에 그려진다. 이 그래프에서 가장 높은 X/Q 값으로부터 시작하여 이 점으로부터 10개의 X/Q을 포함하는 영역내의 모든 다른 점 사이의 경사를 비교하여 가장 작은 음의 경사를 갖는 선을 생성하는 계수들이 저장되며, 이 선의 끝점이 다음 영역의 시작점으로 이용되어 반복적으로 선이 그려진다. 이와 같이 그려진 선을 이용하여 누적빈도 0.5%, 5% 혹은 50%에 상응하는 X/Q 값이 계산되어, 사고 후 $0{\sim}2$ 시간의 X/Q 값으로 이용되며 매우 보수적인 경향을 갖게 된다. 본 논문에서는 퍼지 논리 추론계통을 이용하여 누적빈도에 대한 X/Q 값의 비선형 보간을 수행하였다. 퍼지 논리 추론계통은 비선형 보간을 위해 탁월한 방법으로 알려져 있다. 제안된 방법을 영광 원자력발전소의 잠재적 방사성물질 누출에 적용한 결과, 좀 더 현실적인 값을 제공하는 것으로 확인되었다.