• 제목/요약/키워드: long-term prediction

검색결과 921건 처리시간 0.029초

매립장의 발생가스특성을 이용한 매립장 침하예측 (Prediction of Landfill Settlement Using Gas Generation Characteristics)

  • 안태봉;박대효;공인철
    • 한국지반공학회논문집
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    • 제20권8호
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    • pp.29-39
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    • 2004
  • 폐기물 매립지의 침하량을 예측하는 것은 우리나라와 같은 좁은 국토를 효율적으로 관리하기 위하여 매우 중요하다. 매립장내 유기물이 장기간에 걸쳐 생화학적으로 분해되기 때문에 압밀이론으로 해석하기 곤란하다. 본 연구에서는 실내모델실험을 통하여 매립가스의 발생특성을 분석하였다. 두개의 시험매립조를 만들었는데 하나는 침출수를 재순환한 것과 다른 하나는 재순환하지 않은 것이다. 시간의 변화에 따른 가스발생량과 매립조의 침하량과의 관계를 분석하였다. 수학적 침하량예측모델을 제안하여 장기침하량을 예측하여 실험계측치와 비교하고 수정계수를 사용하도록 제안하였다. 침출수 재순환이 침하를 촉진하는 효과가 있는 것으로 나타났는데 가스모델의 수정계수가 침출수순환을 하지 않은 경우는 1.4, 재순환한 경우는 1.7으로서 약 22%의 촉진효과가 있다.

Dynamic Susceptibility Contrast (DSC) Perfusion MR in the Prediction of Long-Term Survival of Glioblastomas (GBM): Correlation with MGMT Promoter Methylation and 1p/19q Deletions

  • Kwon, Yong Wonn;Moon, Won-Jin;Park, Mina;Roh, Hong Gee;Koh, Young Cho;Song, Sang Woo;Choi, Jin Woo
    • Investigative Magnetic Resonance Imaging
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    • 제22권3호
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    • pp.158-167
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    • 2018
  • Purpose: To investigate the surgical, perfusion, and molecular characteristics of glioblastomas which influence long-term survival after treatment, and to explore the association between MR perfusion parameters and the presence of MGMT methylation and 1p/19q deletions. Materials and Methods: This retrospective study was approved by our institutional review board. A total 43 patients were included, all with pathologic diagnosis of glioblastoma with known MGMT methylation and 1p/19q deletion statuses. We divided these patients into long-term (${\geq}60\;months$, n = 7) and short-term (< 60 months, n = 36) survivors, then compared surgical extent, molecular status, and rCBV parameters between the two groups using Fisher's exact test or Mann-Whitney test. The rCBV parameters were analyzed according to the presence of MGMT methylation and 1p/19q deletions. We investigated the relationship between the mean rCBV and overall survival using linear correlation. Multivariable linear regression was performed in order to find the variables related to overall survival. Results: Long-term survivors (100% [7 of 7]) demonstrated a greater percentage of gross total or near total resection than short-term survivors (54.5% [18 of 33]). A higher prevalence of 1p/19q deletions was also noted among the long-term survivors (42.9% [3 of 7]) than the short-term survivors (0.0% [0 of 36]). The rCBV parameters did not differ between the long-term and short-term survivors. The rCBV values were marginally lower in patients with MGMT methylation and 1p/19q deletions. Despite no correlation found between overall survival and rCBV in the whole group, the short-term survivor group showed negative correlation ($R^2=0.181$, P = 0.025). Multivariable linear regression revealed that surgical extent and 1p/19q deletions, but not rCBV values, were associated with prolonged overall survival. Conclusion: While preoperative rCBV and 1p/19q deletion status are related to each other, only surgical extent and the presence of 1p/19q deletion in GBM patients may predict long-term survival.

Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities

  • Kim, Sun-Young;Yi, Seon-Ju;Eum, Young Seob;Choi, Hae-Jin;Shin, Hyesop;Ryou, Hyoung Gon;Kim, Ho
    • Environmental Analysis Health and Toxicology
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    • 제29권
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    • pp.12.1-12.8
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    • 2014
  • Objectives Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to $10{\mu}m$ in diameter ($PM_{10}$) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. Methods We obtained hourly $PM_{10}$ data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average $PM_{10}$ concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared ($R^2$) statistics were computed. Results Mean annual average $PM_{10}$ concentrations in the seven major cities ranged between 45.5 and $66.0{\mu}g/m^3$ (standard deviation=2.40 and $9.51{\mu}g/m^3$, respectively). Cross-validated $R^2$ values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had $R^2$ values of zero. The national model produced a higher cross-validated $R^2$ (0.36) than those for the city-specific models. Conclusions In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate $PM_{10}$ source characteristics.

미래 기상정보를 사용하지 않는 LSTM 기반의 피크시간 태양광 발전량 예측 기법 (A LSTM Based Method for Photovoltaic Power Prediction in Peak Times Without Future Meteorological Information)

  • 이동훈;김관호
    • 한국전자거래학회지
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    • 제24권4호
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    • pp.119-133
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    • 2019
  • 최근 태양광 발전량 예측은 태양광 발전량 설비 시스템의 안정적인 작동을 위한 조정 계획, 설비 규격 결정 및 생산 계획 일정을 수립하기 위해 필수적인 요소로 고려된다. 특히, 대부분의 태양광 발전량은 피크시간에 측정되기 때문에, 태양광 시스템 운영자의 이익 최대화와 전력 계통량 안정화를 위해 피크시간의 태양광 발전량 예측은 매우 중요한 요소이다. 또한, 기존 연구들은 광범위한 지역에서 예측된 불확실한 기후 정보들을 이용하여 태양광 발전량을 예측하는 한계점 때문에 일사량, 운량, 온도 등과 기상정보 없이 피크시간의 태양광 발전량을 예측하는 것은 매우 어려운 문제로 고려된다. 따라서 본 논문에서는 피크이전의 기후, 계절 및 관측된 태양광 발전량을 이용하여 미래의 기후 및 계절 정보 없이 피크시간의 태양광 발전량을 예측할 수 있는 LSTM(Long-Shot Term Memory) 기반의 태양광 발전량 예측 기법을 제안한다. 본 연구에서 제안한 모델을 기반으로 실 데이터를 통한 실험 결과, 단기 및 장기적 관점에서 높은 성능을 보였으며, 이는 본 연구에서 목표로 한 피크시간의 태양광 발전량 예측 성능 향상에 긍정적인 영향을 나타내었음을 보여준다.

DNN 및 LSTM 기반 딥러닝 모형을 활용한 태화강 유역의 수위 예측 (Water level prediction in Taehwa River basin using deep learning model based on DNN and LSTM)

  • 이명진;김종성;유영훈;김형수;김삼은;김수전
    • 한국수자원학회논문집
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    • 제54권spc1호
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    • pp.1061-1069
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    • 2021
  • 최근 이상 기후로 인해 극한 호우 및 국지성 호우의 규모 및 빈도가 증가하여 하천 주변의 홍수 피해가 증가하고 있다. 이에 따라 하천 또는 유역 내 수문학적 시스템의 비선형성이 증가하고 있으며, 기존의 물리적 기반의 수문 모형을 활용하여 홍수위를 예측하기에는 선행시간이 부족한 한계점이 존재한다. 본 연구에서는 Deep Neural Network (DNN) 및 Long Short-Term Memory (LSTM)기반의 딥러닝 기법을 적용하여 울산시(태화교) 지점의 수위를 0, 1, 2, 3, 6, 12시간에 대해 선행 예측을 수행하였고 예측 정확도를 비교 분석하였다. 그 결과 sliding window 개념을 적용한 DNN 모형이 선행시간 12시간까지 상관계수 0.97, RMSE 0.82 m로 가장 높은 정확도를 보이고 있음을 확인하였다. 향후 DNN 모형을 활용하여 딥러닝 기반의 수위 예측을 수행한다면 기존의 물리적 모형을 통한 홍수위 예측보다 향상된 예측 정확도와 충분한 선행시간을 확보할 수 있을 것으로 판단된다.

고온 크리프 구조물의 장시간 한계응력강도 예측 (Prediction of Long-Term Stress Intensity Limit of High-Temperature Creep Structures)

  • 김우곤;류우석;김현희
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 춘계학술대회
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    • pp.648-653
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    • 2003
  • In order to predict stress intensity limit of high-temperature creep structures, creep work-time equation, defined as $W_ct^P=B$, was used, and the results of the equation were compared with isochronous stress-strain curve (ISSC) ones of ASME BPV NH Code. For this purpose, the creep strain tests with. time variations for commercial type 316 stainless steel were conducted with different stresses; 160 MPa, 150 MPa, 145 MPa, 140 MPa and 135 MPa at $593^{\circ}C$. The results of log $W_c$ and log t plots showed a good linear relation up to $10^5$ hr. The constants p, B and stress intensity limit values showed comparatively good agreement to those of ASME NH ISSC. It is believed that the relation can be simply obtained with only several short-term 1% strain data without ISSC which can be obtained by long-term creep data.

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콘크리트에 도포된 도막의 투기계수 측정을 통한 장기 중성화 깊이 예측 (Prediction of Long-Term Carbonation Depth by Measurement of the Air Permeability Coefficient of Coating on Concrete)

  • 박동천;남민석;김용로;고효진;류동우
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2023년도 봄 학술논문 발표대회
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    • pp.113-114
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    • 2023
  • This study measured the thickness and speculation coefficient of the coating for existing buildings and calculated the diffusion coefficient of the coating to predict the depth of carbonation through numerical analysis in order to evaluate the impact of the external finish and local environment. As a result, it was possible to predict the short-term and long-term carbonation depth of reinforced concrete buildings coated with coating film with considerable reliability.

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측정-상관-예측법을 이용한 장기간 풍속 및 설비이용률의 예측 (Prediction of long-term wind speed and capacity factor using Measure-Correlate-Predict method)

  • 고경남;허종철
    • 한국태양에너지학회 논문집
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    • 제32권6호
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    • pp.37-43
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    • 2012
  • Long-term variations in wind speed and capacity factor(CF) on Seongsan wind farm of Jeju Island, South Korea were derived statistically. The selected areas for this study were Subji, having a year wind data at 30m above ground level, Sinsan, having 30-year wind data at 10m above ground level and Seongsan wind farm, where long-term CF was predicted. The Measure-Correlate-Predict module of WindPRO was used to predict long-tem wind characteristics at Seongsan wind farm. Eachyear's CF was derived from the estimated 30-year time series wind data by running WAsP module. As a result, for the 30-year CFs, Seongsan wind farm was estimated to have 8.3% for the coefficien to fvariation, CV, and-16.5% ~ 13.2% for the range of variation, RV. It was predicted that the annual CF at Seongsan wind farm varied within about ${\pm}4%$.

Bass 확산모형을 활용한 국내 주택연금의 중·장기 수요예측 (Long-Term Projection of Demand for Reverse Mortgage Using the Bass Diffusion Model in Korea)

  • 양진아;민대기;최형석
    • 한국경영과학회지
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    • 제42권1호
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    • pp.29-41
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    • 2017
  • Korea is expected to become a super-aged society by 2050. Given an aging population and the increasing pressure for the early retirement, a sufficient social safety net for elderly population becomes important. The Korean government introduced public reverse mortgage program in 2007, which is a product for aging seniors and the elderly, The number of reverse mortgage subscribers has also steadily grown. The demand continues to grow, but the reverse mortgage over a long period of time is a highly uncertain and risky product in the position of guarantee or lending institution. Thus, suitable demand prediction of the reverse mortgage subscribers is necessary for stable and sustainable operation. This study uses a Bass diffusion model to forecast the long-term demand for reverse mortgage and provides insight into reverse mortgage by forecasting demand for stability and substantiality of the loan product. We represent the projections of new subscribers on the basis of the data obtained from Korea Housing Finance Corporation. Results show that potential market size of Korean reverse mortgage reaches approximately 760,000-1,160,000 households by 2020. We validate the results by comparing the estimate of the cumulative number of subscribers with that found in literature.

콘크리트 크리프의 확률론적 거동 해석 (The Analysis of Statistical Behavior in Concrete Creep)

  • 김두환;박종철
    • 한국구조물진단유지관리공학회 논문집
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    • 제5권1호
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    • pp.237-246
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    • 2001
  • This study is to measure the creep coefficient by 3 days, 7 days and 28 days in the age when loading for the quality assessment of $350kgf/cm^2$ in the high-strength concrete. And it is to analyze the behavior of creep coefficient by applying the experimental data though the compressive strength test, the elastic modulus test and the dry shrinkage test to the ACI-209, AASHTO-94 and CEB/FIP-90, the prediction mode, and the basis of concrete structural design. Also it is to analyze the behavior of short-term creep coefficient during 91 days in the age when loading through the experiment by using the regression analysis, the statistical theory. As applying it to the long-term behavior during 365 days and comparing with the creep prediction mode and examining it, the result from the analysis of the quality of the concrete is as follows. As the result of comparison and analysis about the ACI-209, AASHTO-94 and CEB/FIP-90, the prediction mode, and the basis of concrete structural design, the normal Portland cement class 1 shows the approximate value with the prediction of GEE/PIP-90 and the basis of concrete structural design, but in case of the prediction of ACI-209 and AASHTO-94, there would be worry of underestimation in the application.

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