• Steel and Composite Structures
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• 제44권1호
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• pp.49-63
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• 2022

This study aims to develop ensemble machine learning (ML) models for estimating the peak floor acceleration and maximum top drift of steel moment frames. For this purpose, random forest, adaptive boosting, gradient boosting regression tree (GBRT), and extreme gradient boosting (XGBoost) models were considered. A total of 621 steel moment frames were analyzed under 240 ground motions using OpenSees software to generate the dataset for ML models. From the results, the GBRT and XGBoost models exhibited the highest performance for predicting peak floor acceleration and maximum top drift, respectively. The significance of each input variable on the prediction was examined using the best-performing models and Shapley additive explanations approach (SHAP). It turned out that the peak ground acceleration had the most significant impact on the peak floor acceleration prediction. Meanwhile, the spectral accelerations at 1 and 2 s had the most considerable influence on the maximum top drift prediction. Finally, a graphical user interface module was created that places a pioneering step for the application of ML to estimate the seismic demands of building structures in practical design.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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• pp.151-152
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• 2021

The sale price of apartment buildings is a key factor in the success or failure of apartment projects, and the factors that affect the sale price of apartments vary widely, including location, environmental factors, and economic conditions. Existing methods of predicting the sale price do not reflect the nonlinear characteristics of apartment prices, which are determined by the complex impact factors of reality, because statistical analysis is conducted under the assumption of a linear model. To improve these problems, a new analysis technique is needed to predict apartment sales prices by complex nonlinear influencing factors. Using machine learning techniques that have recently attracted attention in the field of engineering, it is possible to predict the sale price reflecting the complexity of various factors. Therefore, this study aims to conduct a basic study for the development of a machine learning-based prediction model for apartment sale prices.

• 한국산업융합학회 논문집
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• 제23권6_2호
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• pp.957-969
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• 2020

The primary objective of this study is to develop a determination system for an optimal combination of earthwork equipment that improves the traditional way in convenience, prediction accuracy, and productivity. For this, the following research works are conducted sequentially; 1)literature review, 2)technology development trend analysis, 3)develop a determination system for the optimal combination of earthwork equipment, 4)simulation of a developed system. As a result, core considerations are deducted for the development of a determination system. Furthermore, site simulation is performed using a developed system. Site simulation result, Cluster 1(R1200LC 7㎥, CAT 775G 65ton×2) was selected from 6 clusters because of its production cost (￦491/㎥). It is expected that the application range and impact on the construction industry will be enormous due to the availability of the developed system.

• 한국ITS학회 논문지
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• 제19권1호
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• pp.1-16
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• 2020

4차 산업혁명 시대가 도래함에 따라 빅데이터를 활용하는 딥러닝에 대한 관심이 높아졌으며 다양한 분야에서 딥러닝을 이용한 연구가 활발하게 진행되고 있다. 교통 분야에서도 교통빅데이터를 많이 활용하는 만큼 딥러닝을 연구에 이용한다면 많은 이점이 있을 것이다. 본 연구에서는 통행속도를 예측하기 위하여 딥러닝 기법인 LSTM을 이용한 단기 통행속도 예측 모형을 구축하였다. 예측에 활용한 데이터인 통행속도 데이터가 시계열 데이터인 것을 고려하여 시계열 예측에 적합한 LSTM 모델을 선택하였다. 통행속도를 보다 정확하게 예측하기 위하여 시간적, 공간적 영향을 모두 반영하는 모형을 구축하였으며, 모형은 1시간 이후를 예측하는 단기 예측모형이다. 분석데이터는 서울시 교통정보센터에서 수집한 5분 단위 통행속도를 활용하였고 분석구간은 교통이 혼잡한 강남대로 일부구간으로 선정하여 연구를 수행하였다.

• 환경영향평가
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• 제2권2호
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• pp.1-11
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• 1993

Most developing countries are experiencing rapid urbanization and the associated growth of industry and services. Cities are currently absorbing two-thirds of the total population in the developing world. Korea has about 85 percent of urban dwellers. World population will shift from being predominantly rural to predominantly urban around the turn of the century. Although cities play a key role in development process and make more than a proportionate contribution to national economic growth, especially cities are also the main catalysts of economic growth in developing countries, they can also be unhealthy, inefficient, and inequitable places to live. Most developing countries are increasingly unable to provide basic environmental infrastructure and services, whether in the megacities or in secondary urban centers. Of particular concern is the strain on natural resources brought by the increasing number of people, cars, and factories. They are generating ever greater amounts of urban wastes and emissions. They also exceed the capacity of regulatory authorities to control them and of nature to assimilate them. The environmental consequences are translated into direct negative impacts on human health, the quality of life, the productivity of the city, and the surrounding ecosystems. Environmental degradation threatens the long tenn availability and quality of natural resources critical to economic growth. Cities, with their higher and growing per capita energy use for domestic, industrial, and transport purpose also contribute a disproportionate share of the emission leading to global warming and acid rain. An important priority is to develop strategic approaches for managing the urban environment. The design of appropriate and lasting strategic responses requires first an understanding of the underlying causes of urban environmental deterioration, it is necessary that longer tenn objectives should be set for urban area to avoid irreversible ecological damage and to ensure lasting economic development. As a means to the preventive policies against the adverse effect, environmental impact assessment (EIA) serve to identify a project's possible environmental consequences early enough to allow their being taken into consideration in the decision making process for urban planning. This paper describes some considerations of EIA for urban planning-scoping, assessment process, measurement and prediction of impacts, pollution controls and supervision, and system planning for environmental preservation.

• 한국도로학회논문집
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• 제12권4호
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• pp.1-9
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• 2010

본 연구는 유고로 인한 대기행렬, 통행시간과 같은 혼잡정보를 예측하여 제공하는 것을 목표로 하며, 이것은 교통시설 이용자와 운영자 모두에게 효율적인 대안선택 및 운영을 위한 중요한 요소로 활용된다. 이러한 예측된 사고영향 정보의 제공으로 인하여, 이용자는 유고 구간에 대한 정보를 사전에 인지하여 지체를 최소화 할 수 있고, 운영자는 현재 유고영향을 받을 것으로 예상되는 구간을 효율적으로 관리할 수 있을 것이다. 본 연구에서는 연속류 본선구간에서 단기예측기법을 적용한 유고영향 예측모형을 제안하였다. 본 연구에서 제안한 모형은 MARE를 통하여 상대적인 오차를 비교분석하여, 예측력이 뛰어난 모형을 정립하였다. 본 연구를 시작으로 미시적인 사고영향 예측 모형이 개발된다면 사고발생 시 지체를 최소화하고 사회적인 비용을 줄일 수 있을 것이다.

• 정보과학회 논문지
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• 제42권3호
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• pp.328-340
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• 2015

소프트웨어에 대한 고객의 요구사항은 다양한 이유로 인해 지속적으로 변화하며, 그로 인해 소프트웨어 개발 시 변경은 불가피한 작업이다. 요구사항에 대한 변경 요청이 발생하는 경우, 변경의 파급 효과를 정확하게 예측하는 것은 효율적인 변경 관리를 위해 매우 중요하다. 본 논문은 객체지향 개발 시 적용할 수 있는 추적성 정보의 관리 방법과 시스템을 구성하는 각 산출물들의 추적성 정보를 바탕으로 변경의 파급효과를 예측하기 위한 영향 분석 지침을 제시한다. 객체지향 시스템을 구성하는 주요 산출물들에 대해서 추적의 대상이 되는 추적 항목들을 식별하고, 그것들의 연관 관계를 정의한다. 추적 항목들의 연관 관계를 기반으로 변경의 파급 효과를 순방향 및 역방향으로 추적하고, 분석할 수 있는 가이드라인을 제시함으로써, 정확한 변경의 범위를 식별하는 것이 본 논문이 제안하는 방법의 목적이다.

• 한국환경복원기술학회지
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• 제20권4호
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• pp.29-42
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• 2017

As the "Guidelines for GHG Environmental Assessment" was revised, it pointed out that the developers should evaluate GHG sequestration and storage of the developing site. However, the current guidelines only taking into account the quantitative reduction lost within the development site, and did not consider the qualitative decrease in the carbon sequestration capacity of forest edge produced by developments. In order to assess the quantitative and qualitative effects of vegetation carbon uptake, the CASA-NPP model and satellite image spatial-temporal fusion were used to estimate the annual net primary production in 2005 and 2015. The development projects between 2006 and 2014 were examined for evaluate quantitative changes in development site and qualitative changes in surroundings by development types. The RMSE value of the satellite image fusion results is less than 0.1 and approaches 0, and the correlation coefficient is more than 0.6, which shows relatively high prediction accuracy. The NPP estimation results range from 0 to $1335.53g\;C/m^2$ year before development and from 0 to $1333.77g\;C/m^2$ year after development. As a result of analyzing NPP reduction amount within the development area by type of forest development, the difference is not significant by type of development but it shows the lowest change in the sports facilities development. It was also found that the vegetation was most affected by the edge vegetation of industrial development. This suggests that the industrial development causes additional development in the surrounding area and indirectly influences the carbon sequestration function of edge vegetaion due to the increase of the edge and influx of disturbed species. The NPP calculation method and results presented in this study can be applied to quantitative and qualitative impact assessment of before and after development, and it can be applied to policies related to greenhouse gas in environmental impact assessment.

• 한국환경복원기술학회지
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• 제24권6호
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• pp.49-65
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• 2021

Although the Environmental Impact Assessment (EIA) is continuously being advanced, the number of environmental disputes regarding it is still on the rise. In order to supplement this, it is necessary to analyze the accumulated complaint cases. In this study, through the analysis of complaint cases, it is possible to identify matters that need to be improved in the existing EIA stages as well as various damages and conflicts that were not previously considered or predicted. In the process, we dervied 'complaint-based data demands' that should be additionally examined to improve the EIA. To this end, a total of 348 news articles were collected by searching with combinations of 'environmental impact assessment' and a keyword for each of the six assessment groups. As a result of analysis of collected data, a total of 54 complaint-based data demands were suggested. Among those were 15 items including 'impact of changes in seawater flow on water quality' in the category of water environment; 13 items including 'area of green buffer zone' in atmospheric environment; 10 items including 'impact of soundproof wall on wind corridor' in living environment; 8 items including 'expected number of users' in socioeconomic environment, 4 items including 'feasibility assessment of development site in terms of environmental and ecological aspects' in natural ecological environment; and 4 items including 'prediction of sediment runoff and damaged areas according to the increase in intensity and frequency of torrential rain' in land environment. In future research, more systematic complaint collection and analysis as well as specific provision methods regarding stages, subjects, and forms of use should be sought to apply the derived data demands in the actual EIA process. It is expected that this study can serve to advance the prediction and assessment of EIA in the future and to minimize environmental impact as well as social conflict in advance.

• 전기학회논문지P
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• 제61권4호
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• pp.174-179
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• 2012

The social and economic level of damages might be highly increased in the case of wide-area black-outages, because of heavy dependence of electricity. Therefore, the development of a wide-area protection relay intelligence techniques is required to prevent massive power outages and minimize the impact strength at failure. The frequency monitoring and prediction for wide-area protection relaying intelligence has been considered as an important technology. In this paper, a network-based frequency monitoring system developed for wide-area protection relay intelligence is presented. In addition, conventional techniques for frequency estimation are compared, and a method for advanced frequency estimation and measurement to improve the precision is proposed. Finally, an integrated monitoring system called K-FNET(Korea-Frequency Monitoring Network) is implemented based on the GPS and various energy monitoring cases are studied.