• Title/Summary/Keyword: Probabilistic Sensitivity Analysis

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Simulation-Based Stochastic Markup Estimation System $(S^2ME)$ (시뮬레이션을 기반(基盤)으로 하는 영업이윤율(營業利潤率) 추정(推定) 시스템)

  • Yi, Chang-Yong;Kim, Ryul-Hee;Lim, Tae-Kyung;Kim, Wha-Jung;Lee, Dong-Eun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2007.11a
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    • pp.109-113
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    • 2007
  • This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation methods were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, bidding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors' B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors' bidding behavior so that the reliability was improved by estimating the output obtained from simulation experiment.

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Formation Estimation of Shaly Sandstone Reservoir using Joint Inversion from Well Logging Data (복합역산을 이용한 물리검층자료로부터의 셰일성 사암 저류층의 지층 평가)

  • Choi, Yeonjin;Chung, Woo-Keen;Ha, Jiho;Shin, Sung-ryul
    • Geophysics and Geophysical Exploration
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    • v.22 no.1
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    • pp.1-11
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    • 2019
  • Well logging technologies are used to measure the physical properties of reservoirs through boreholes. These technologies have been utilized to understand reservoir characteristics, such as porosity, fluid saturation, etc., using equations based on rock physics models. The analysis of well logs is performed by selecting a reliable rock physics model adequate for reservoir conditions or characteristics, comparing the results using the Archie's equation or simandoux method, and determining the most feasible reservoir properties. In this study, we developed a joint inversion algorithm to estimate physical properties in shaly sandstone reservoirs based on the pre-existing algorithm for sandstone reservoirs. For this purpose, we proposed a rock physics model with respect to shale volume, constructed the Jacobian matrix, and performed the sensitivity analysis for understanding the relationship between well-logging data and rock properties. The joint inversion algorithm was implemented by adopting the least-squares method using probabilistic approach. The developed algorithm was applied to the well-logging data obtained from the Colony gas sandstone reservoir. The results were compared with the simandox method and the joint inversion algorithms of sand stone reservoirs.

Probabilistic Medium- and Long-Term Reservoir Inflow Forecasts (II) Use of GDAPS for Ensemble Reservoir Inflow Forecasts (확률론적 중장기 댐 유입량 예측 (II) 앙상블 댐 유입량 예측을 위한 GDAPS 활용)

  • Kim, Jin-Hoon;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.39 no.3 s.164
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    • pp.275-288
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    • 2006
  • This study develops ESP (Ensemble Streamflow Prediction) system by using medium-term numerical weather prediction model which is GDAPS(T213) of KMA. The developed system forecasts medium- and long-range exceedance Probability for streamflow and RPSS evaluation scheme is used to analyze the accuracy of probability forecasts. It can be seen that the daily probability forecast results contain high uncertainties. A sensitivity analysis with respect to forecast time resolution shows that uncertainties decrease and accuracy generally improves as the forecast time step increase. Weekly ESP results by using the GDAPS output with a lead time of up to 28 days are more accurately predicted than traditional ESP results because conditional probabilities are stably distributed and uncertainties can be reduced. Therefore, it can be concluded that the developed system will be useful tool for medium- and long-term reservoir inflow forecasts in order to manage water resources.

A Study on the Effects of Reading Education Using Book-Coding (북코딩의 독서교육 효과에 관한 연구)

  • Ji, Hyoun-Ah;Cho, Miah
    • Journal of Korean Library and Information Science Society
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    • v.52 no.2
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    • pp.145-166
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    • 2021
  • The study was aimed at verifying the effectiveness of Book-Coding reading education as a reader activity of older elementary school children at a time when high-dimensional thinking abilities were formed. To this end, 30 fifth-grade children of N Elementary School in N-si, Gyeonggi-do, comprised of 15 students from a reading education program using Book-Coding, and 15 students from a reading comprehension program, and applied the reading education program over a total of 12 sessions. The main results of the study are summarized as follows. First, when the effects of the convergence reading education program using Book-Coding on the logical thinking ability of the students in the upper grades in the elementary school were analyzed, all the six sub-factors of logical thinking ability, that is, conservation logic, proportional logic, variable controlling logic, probabilistic logic, correlational inference logic, and combinational logic, were proved to have statistically more meaningful difference than the group writing a book report. Second, the analysis result of the influence of the convergence reading education program using Book-Coding on the creativity of the students in the upper grades of the elementary school showed that all the 13 elements of curiosity, persistence, effectiveness, independence, adventurousness, openness, knowledge, imagination, originality, sensitivity, fluency, flexibility, and accuracy were statistically meaningfully different compared to the book report group. Third, when it was analyzed how the convergence reading education program using Book-Coding affected the creative personality of the elementary school students, all the six factors of curiosity, task commitment, independence, awareness of risk, and openness of thinking, and aesthetics were found out to have a statistically more meaningful difference than the group that wrote a book report.

Prediction of Expected Residual Useful Life of Rubble-Mound Breakwaters Using Stochastic Gamma Process (추계학적 감마 확률과정을 이용한 경사제의 기대 잔류유효수명 예측)

  • Lee, Cheol-Eung
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.31 no.3
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    • pp.158-169
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    • 2019
  • A probabilistic model that can predict the residual useful lifetime of structure is formulated by using the gamma process which is one of the stochastic processes. The formulated stochastic model can take into account both the sampling uncertainty associated with damages measured up to now and the temporal uncertainty of cumulative damage over time. A method estimating several parameters of stochastic model is additionally proposed by introducing of the least square method and the method of moments, so that the age of a structure, the operational environment, and the evolution of damage with time can be considered. Some features related to the residual useful lifetime are firstly investigated into through the sensitivity analysis on parameters under a simple setting of single damage data measured at the current age. The stochastic model are then applied to the rubble-mound breakwater straightforwardly. The parameters of gamma process can be estimated for several experimental data on the damage processes of armor rocks of rubble-mound breakwater. The expected damage levels over time, which are numerically simulated with the estimated parameters, are in very good agreement with those from the flume testing. It has been found from various numerical calculations that the probabilities exceeding the failure limit are converged to the constraint that the model must be satisfied after lasting for a long time from now. Meanwhile, the expected residual useful lifetimes evaluated from the failure probabilities are seen to be different with respect to the behavior of damage history. As the coefficient of variation of cumulative damage is becoming large, in particular, it has been shown that the expected residual useful lifetimes have significant discrepancies from those of the deterministic regression model. This is mainly due to the effect of sampling and temporal uncertainties associated with damage, by which the first time to failure tends to be widely distributed. Therefore, the stochastic model presented in this paper for predicting the residual useful lifetime of structure can properly implement the probabilistic assessment on current damage state of structure as well as take account of the temporal uncertainty of future cumulative damage.