• Title/Summary/Keyword: 장래 예측

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A Markov Chain Model for Population Distribution Prediction Considering Spatio-Temporal Characteristics by Migration Factors (이동요인별 시·공간적 인구이동 특성을 고려한 인구분포 예측: 마르코프 연쇄 모형을 활용하여)

  • Park, So Hyun;Lee, Keumsook
    • Journal of the Economic Geographical Society of Korea
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    • v.22 no.3
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    • pp.351-365
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    • 2019
  • This study aims to predict the changes in population distribution in Korea by considering spatio-temporal characteristics of major migration reasons. For the purpose, we analyze the spatio-temporal characteristics of each major migration reason(such as job, family, housing, and education) and estimate the transition probability, respectively. By appling Markov chain model processes with the ChapmanKolmogorov equation based on the transition probability, we predict the changes in the population distribution for the next six years. As the results, we found that there were differences of population changes by regions, while there were geographic movements into metropolitan areas and cities in general. The methodologies and the results presented in this study can be utilized for the provision of customized planning policies. In the long run, it can be used as a basis for planning and enforcing regionally tailored policies that strengthen inflow factors and improve outflow factors based on the trends of population inflow and outflow by region by movement factors as well as identify the patterns of population inflow and outflow in each region and predict future population volatility.

A Comparative Study on the Prediction of the Final Settlement Using Preexistence Method and ARIMA Method (기존기법과 ARIMA기법을 활용한 최종 침하량 예측에 관한 비교 연구)

  • Kang, Seyeon
    • Journal of the Korean GEO-environmental Society
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    • v.20 no.10
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    • pp.29-38
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    • 2019
  • In stability and settlement management of soft ground, the settlement prediction technology has been continuously developed and used to reduce construction cost and confirm the exact land use time. However, the preexistence prediction methods such as hyperbolic method, Asaoka method and Hoshino method are difficult to predict the settlement accurately at the beginning of consolidation because the accurate settlement prediction is possible only after many measurement periods have passed. It is judged as the reason for estimating the future settlement through the proportionality assumption of the slope which the preexistence prediction method computes from the settlement curve. In this study, ARIMA technique is introduced among time series analysis techniques and compared with preexistence prediction methods. ARIMA method was predictable without any distinction of ground conditions, and the results similar to the existing method are predicted early (final settlement).

Time Series Model을 이용한 주요항만 해상교통량 예측

  • Yu, Sang-Rok;Jeong, Jung-Sik;Kim, Cheol-Seung;Jeong, Jae-Yong
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2013.10a
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    • pp.133-135
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    • 2013
  • 장래의 해상교통량에 대한 정확한 예측은 항로설계 및 해상교통의 안전성 평가 측면에서 중요한 요소이다. 본 연구는 신뢰성 있는 해상교통량을 추정하기 위해 시계열 모델의 지수평활법과 ARIMA 모형을 이용하여 모형의 식별 및 진단 방안을 제시하였다. 제시된 방법의 효과를 검증하기 위하여 주요항만인 부산항, 광양항, 인천항, 평택항의 해상교통량을 예측하였다. 그 결과로 부산항은 ARIMA 모형, 광양항은 Winters 승법 모형, 인천항은 단순계절 모형, 평택항은 ARIMA 모형이 더 적합한 모형으로 알 수 있었으며, 각 항만별 계절에 따라 월별 교통량의 차이를 보이는 것으로 분석되었다. 본 연구 결과는 향후 항로 및 항만설계 또는 해상교통 안전성 평가에 보다 신뢰성 있는 추정치를 제공할 수 있을 것으로 보인다.

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Development of a Technique for Estimating Ground Water Level Using Daily Precipitation Data (일강우자료를 활용한 지하수위 예측기법 개발)

  • Park, Jae-Hyeon;Choi, Young-Sun;Park, Chang-Kun;Yang, Jung-Suk;Booh, Seong-An
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.189-193
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    • 2006
  • 대체용수원의 개발이 시급하게 대두되어지고 있는 가운데 제한된 수자원을 보다 효과적으로 사용하기 위한 하나의 방법으로 지하댐(Groundwater Dam) 건설을 이용한 지하수 자원의 개발이 하나의 방법으로 제안되었다. 하지만 해안지역에 설치된 지하댐을 운영할 경우 지하수위 변동에 따른 염수의 침입을 고려하여 운영하여야 한다. 특히 갈수시는 지하수위 하강이 강하게 나타나는 시기로 지하수위는 지하댐 최적운영을 위한 중요한 지표가 된다. 특히 강우량 자료를 활용한 가뭄지수와 지하수위의 관계를 설명 할 수 있다면 예상 강우자료를 활용한 장래의 지하수위를 예측 할 수 있으며 이것은 지하댐 운영에 매우 효과적으로 활용 할 수 있을 것이다. 본 연구에서는 기존의 강우와 예상 강우 자료를 활용하여 지하수위 예측기법을 개발하였다. 과거 강수량의 일이동 평균값을 바탕으로 한 다항 회귀모델을 수립하여, 계절적 특성을 고려한 구간을 분리하여 적용하였다. 예측된 지하수위의 정확성을 알아보기 위해 관측된 지하수위와 예측된 지하수위를 비교 분석하였다. 분석 결과 단순회귀기법을 지하수위를 예측한 경우 $0.62{\sim}0.63$의 상관계수를 보인반면 다항회귀기법을 적용한 결과 $0.62{\sim}0.84$로 상관계수가 증가하였다. 대체적으로 관측된 지하수위와 예측된 지하수위는 비슷한 경향을 보였다. 따라서 지하댐 운영에 있어 최적의 취수량을 개발하기위해 일강우자료를 활용한 지하수위 예측기법의 활용성은 매우 높은 것으로 판단된다.

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The Prediction Model Development for Water Supply Monitoring System based on Machine Learning (머신러닝을 고려한 상수도 모니터링 시스템 예측 모델 개발)

  • Shim, Kyu Dae;Choung, Joon Yeon;Kim, Chang Ryong;Kim, Dong Kyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.395-395
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    • 2022
  • 본 연구는 머신러닝 기반의 상수도 모니터링 시스템의 예측 모델을 개발하고, 예측 모델의 적용이 가능성을 검토하였다. 상수도모니터링 시스템은 상수관망에 설치된 센서에서 수집된 자료를 모니터링 할 수 있어 운영자의 상수도 시설물의 관리 편의성을 높일 수 있다. 특히 수리학적 모델을 적용하여 계산된 값과 측정된 값을 비교해 이상치가 발생하면 운영자에게 이를 알려주므로 시스템내의 문제점을 빠르게 확인할 수 있다. 그러나 수리학적 모델은 입력자료가 증가됨에 따라 계산시간이 많이 소요되는 문제가 있고, 계산된 값의 정확도가 낮아지므로. 이러한 문제를 보완하기 위해 머신러닝 기반의 예측 모델을 개발하여 이를 해결하고자 하였다. 예측 모델은 GS 이니마 브라질(GS Inima Brazil)에서 운영중인 아라사투바(Aracatuba) 지역 주사라(Jussara) DMA(District Metered Area)의 2018년 1월에서 7월까지의 운영자료를 이용하였으며, 상수도 모니터링 시스템에서 상수관로 수압에 영향을 미치는 영향 인자들을 분석하고, 하이퍼파라미터 최적화를 통한 수압 예측 모델을 개선하였다. 금회 연구는 머신러닝 기반의 모델을 통하여 상수관망의 시간변화에 따른 장래 예측 수압을 검토할 수 있었다는데 큰 의의가 있다.

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Development of Fertility Assumptions for the Future Population Projection (장래인구추계를 위한 출산력 가정치의 설정)

  • Jun, Kwang-Hee
    • Korea journal of population studies
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    • v.29 no.2
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    • pp.53-88
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    • 2006
  • The major aim of this paper is to develop a hypothetical set of age-specific fertility rates which are logically derived and reasonably accurate in the projection of future population. The first procedure is to select a generalized log-gamma distribution model, which includes Coale-McNeil nuptiality model, in order to estimate and project a set of age-specific fertility rates by birth cohort and birth order. The second is to apply the log-gamma model with an empirical adjustment to the actual data to estimate and project the future fertility rates for relatively young birth cohorts who did not complete their reproductive career. This study reconstructs or translates a set of cohort age-specific fertility rates into a set of period age-specific fertility rates which must be hypothesized in order to establish the broader framework of future population projection. For example, the fertility at age 20 in the year of 2020 is the fertility at age 20 for the cohort born in 1990, while the fertility at age 21 in the year of 2020 is the fertility at 21 for the cohort born in 1989. In turn, once a set of age-specific fertility rates for the cohorts who were born up to the year of 2010, it is possible for one to establish an hypothetical set of period age-specific fertility rates which will be needed to project the future population until the year of 2055. The difference in the hypothetical system of age-specific fertility rates between this study and the 2005 special population projection comes from the fact that the fertility estimation/projection model used in this study was skillfully exploited to reflect better actual trend of fertility decline caused by rise in marriage age and increasing proportion of those who remain single until their end of reproduction. In this regard, this paper argues that the set of age-specific fertility rates derived from this study is more logical and reasonably accurate than the set of those used for the 2005 special projection. In the population projection, however, the fundamental issue of the hypothetical setting of age-specific fertility rates in relation to the fertility estimation/projection model is about how skillfully one can handle the period effects. It is not easy for one to completely cope with the problem of period effects except for the a minor period adjustment based on recent actual data, along with the given framework of a cohort-based fertility estimation/projection model.

Developing a Method for Estimating Urban Environmental Impact Using an Integrated Land Use-Transport Model (토지이용-교통 통합 모형을 활용한 도시 환경 영향 예측 방법론 개발)

  • HU, Hyejung;YANG, Choongheon;YOON, Chunjoo;KIM, Insu;SUNG, Junggon
    • Journal of Korean Society of Transportation
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    • v.33 no.3
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    • pp.294-303
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    • 2015
  • This paper describes a method that can be used for estimating future carbon emissions and environmental effects. To forecast future land use and transportation changes under various low carbon policies, a DELTA and OmniTRANS combination (a land use-transport integrated model) was applied. Appropriate emission estimation methods and dispersion models were selected and applied in the method. It was designed that the estimated emissions from land use and transportation activity as well as the estimated concentrations of air pollutants and comprehensive air quality index (CAI) are presented on a GIS-based map. The prototype was developed for the city of Suwon and the outcome examples were presented in this paper; it demonstrates what kinds of analysis results are presented in this method. It is expected that the developed method will be very useful for decision makers who want to know the effect of environmental policies in cities.

Prediction of Life Expectancy of Asphalt Road Pavement by Region (아스팔트 도로포장의 균열률에 대한 지역별 기대수명 추정)

  • Song, Hyun Yeop;Choi, Seung Hyun;Han, Dae Seok;Do, Myung Sik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.41 no.4
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    • pp.417-428
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    • 2021
  • Since future maintenance cost estimation of infrastructure involves uncertainty, it is important to make use of a failure prediction model. However, it is difficult for local governments to develop accurate failure prediction models applicable to infrastructure due to a lack of budget and expertise. Therefore, this study estimated the life expectancy of asphalt road pavement of national highways using the Bayesian Markov Mixture Hazard model. In addition, in order to accurately estimate life expectancy, environmental variables such as traffic volume, ESAL (Equivalent Single Axle Loads), SNP (Structural Number of Pavement), meteorological conditions, and de-icing material usage were applied to retain reliability of the estimation results. As a result, life expectancy was estimated from at least 13.09 to 19.61 years by region. By using this approach, it is expected that it will be possible to estimate future maintenance cost considering local failure characteristics.

Development of a Trip Distribution Model by Iterative Method Based on Target Year's O-D Matrix (통행분포패턴에 기초한 장래 O-D표 수렴계산방법 개발)

  • Yu, Yeong-Geun
    • Journal of Korean Society of Transportation
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    • v.23 no.2
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    • pp.143-150
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    • 2005
  • Estimation of trip distribution, estimated O-D matrix must satisfy the condition that the sum of trips in a row should equal the trip production, and the sum of trips in a column should equal the trip attraction. In most cases the iterative calculation for convergence is needed to satisfy this condition. Most of all present convergence of iterative methods may results a big difference between estimated value and converged value, and from this, the trip distribution patterns may be changed. This paper presents a new convergence of iterative method that comes closer to meeting the convergence condition and gives the maximum likelihood estimation for calculating a distribution patterns from the trip distribution estimation model. The newly developed method differs from existing methods in three important ways. First, it simultaneously considers both the convergence condition and the distribution patterns. Second, it computers simultaneous convergence of rows and columns instead of iterating respectively. Third, instead of using the growth rates to the trip production, trip attraction, it uses the differences between trip production and sum of trips in a row, and trip attraction and sum of trips in a column. Using 38 by 38 O-D matrix, this paper compared the Fratar method and the Furness method to the newly developed method and found that this method was superior to the other two methods.

Development of web-based system for ground excavation impact prediction and risk assessment (웹기반 굴착 영향도 예측 및 위험도 평가 시스템 개발)

  • Park, Jae Hoon;Lee, Ho;Kim, Chang Yong;Park, Chi Myeon;Kim, Ji Eun
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.6
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    • pp.559-575
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    • 2021
  • Due to the increase in ground excavation work, the possibility of ground subsidence accidents is increasing. And it is very difficult to prevent these risk fundamentally through institutional reinforcement such as the special law for underground safety management. As for the various cases of urban ground excavation practice, the ground subsidence behavior characteristics which is predicted using various information before excavation showed a considerable difference that could not be ignored compared to the results real construction data. Changes in site conditions such as seasonal differences in design and construction period, changes in construction methods depending on the site conditions and long-term construction suspension due to various reasons could be considered as the main causes. As the countermeasures, the safety management system through various construction information is introduced, but there is still no suitable system which can predict the effect of excavation and risk assessment. In this study, a web-based system was developed in order to predict the degree of impact on the ground subsidence and surrounding structures in advance before ground excavation and evaluate the risk in the design and construction of urban ground excavation projects. A system was built using time series analysis technique that can predict the current and future behavior characteristics such as ground water level and settlement based on past field construction records with field monitoring data. It was presented as a geotechnical data visualization (GDV) technology for risk reduction and disaster management based on web-based system, Using this newly developed web-based assessment system, it is possible to predict ground excavation impact prediction and risk assessment.