• Computers and Concrete
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• 제14권1호
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• pp.19-40
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• 2014

Reinforced concrete deep beams are structural beams with low shear span-to-depth ratio, and hence in which the strain distribution is significantly nonlinear and the conventional beam theory is not applicable. A strut-and-tie model is considered one of the most rational and simplest methods available for shear strength prediction and design of deep beams. The strut-and-tie model approach describes the shear failure of a deep beam using diagonal strut and truss mechanism: The diagonal strut mechanism represents compression stress fields that develop in the concrete web between diagonal cracks of the concrete while the truss mechanism accounts for the contributions of the horizontal and vertical web reinforcements. Based on a database of 406 experimental observations, this paper proposes a new strut-and-tie-model for accurate prediction of shear strength of reinforced concrete deep beams, and further improves the model by correcting the bias and quantifying the scatter using a Bayesian parameter estimation method. Seven existing deterministic models from design codes and the literature are compared with the proposed method. Finally, a limit-state design formula and the corresponding reduction factor are developed for the proposed strut-andtie model.

• 인터넷정보학회논문지
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• 제12권5호
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• pp.1-9
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• 2011

일반화된 PF 스케줄링을 사용하는 무선이동 네트워크는 스케줄링 변수를 조정하여 동적인 무선 자원 할당을 가능케 한다. 기존의 확률론적 접근 방법으로는 일반적인 환경에서 네트워크의 용량을 예측하는 데에는 한계가 있다. 더욱이 그 한계는 요구되는 네트워크 용량을 얻도록 하는 스케줄링 변수를 효율적으로 찾을 수 없게 한다. 본 논문은 결정론적 접근 방법을 사용하여 네트워크의 용량을 예측하는 알고리즘을 유도한다. 얻어진 용량 예측 알고리즘을 이용하여 요구되는 용량에 따른 스케줄링 변수 설정을 효과적으로 할 수 있는 용량 조정 알고리즘과 용량 교환 알고리즘 제안한다. IEEE 802.16m 시스템 기반 의 시스템 레벨 시뮬레이션을 통해 제안된 용량 예측 알고리즘과 용량 교환 알고리즘의 성능을 확인한다.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권5호
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• pp.169-178
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• 2021

최근 들어 공유자전거 시스템은 대중교통 이용이 어렵거나 불가능한 마지막 목적지까지의 거리인 "라스트 마일"을 해소하는 방안으로 주목받고 있다. 공유자전거 시스템에서는 자전거의 대여와 반납의 불균형으로 인해서 사용자가 원하는 시간에 원하는 대여소에서 자전거를 빌리거나 반납할 수 있는 문제가 자주 발생한다. 이에 자전거 재배치는 공유자전거 시스템을 효율적으로 운영하는데 매우 중요한 이슈이다. 자전거 재배치를 효율적이고 효과적으로 진행하기 위해서는 무엇보다 정확한 수요 예측이 이뤄져야 한다. 최근에는 대여소의 수요를 보다 정확하게 예측하기 위해 군집 기반의 수요 예측 모델을 활용하는 방법이 개발되고 있는데, 여기서는 군집 분석 단계가 매우 중요하다. 이 연구에서는 비결정적이고 수렴이 어려운 기존의 공유자전거 수요 예측을 위한 군집 방법의 단점을 극복하는 k-means 기반의 군집 알고리즘을 제안한다. 이 방법은 초기 중심점 방법을 활용하기 때문에 매번 동일한 결과를 얻을 수 있으며, 대여소의 시간별 반납/대여 비중을 이용하여 기존 방법과는 달리 이전 단계의 군집 결과를 필요로 하지 않아 반복해서 군집 분석을 수행할 필요가 없어 빠른 군집 분석이 가능한 장점이 있다.

• 한국농공학회논문집
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• 제49권4호
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• pp.13-22
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• 2007

The uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modeling system under uncertainty was described and demonstrated for use in watershed management and receiving-water quality prediction. A watershed model (HSPF), a receiving water quality model (WASP), and a wetland model (NPS-WET) were incorporated into an integrated modeling system (modified-BASINS) and applied to the Hwaseong Reservoir watershed. Reservoir water quality was predicted using the calibrated integrated modeling system, and the deterministic integrated modeling output was useful for estimating mean water quality given future watershed conditions and assessing the spatial distribution of pollutant loads. A Monte Carlo simulation was used to investigate the effect of various uncertainties on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorous (T-P) in the Hwaseong Reservoir, considering uncertainty, would be less than about 4.8 and 0.26 mg 4.8 and 0.26 mg $L^{-1}$, respectively, with 95% confidence. The effects of two watershed management practices, a wastewater treatment plant (WWTP) and a constructed wetland (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaseong Reservoir to less than 3.54 and 0.15 mg ${L^{-1}$, 26.7 and 42.9% improvements, respectively, with 95% confidence. Overall, the Monte Carlo simulation in the integrated modeling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on probability and level of risk, and its application is recommended.

• Bioinformatics and Biosystems
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• 제2권1호
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• pp.28-32
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• 2007

The protein phosphorylation is one of the important processes in the cell signaling pathway. A variety of protein kinase families are involved in this process, and each kinase family phosphorylates different kinds of substrate proteins. Many methods to predict the kinase-specific phosphoryrated sites or different types of phosphorylated residues (Serine/Threonine or Tyrosin) have been developed. We employed Supprot Vector Machine (SVM) to attempt the prediction of protein kinase specific phosphorylation sites. 10 different kinds of protein kinase families (PKA, PKC, CK2, CDK, CaM-KII, PKB, MAPK, EGFR) were considered in this study. We defined 9 residues around a phosphorylated residue as a deterministic instance from which protein kinases determine whether they act on. The subsets of PSI-BALST profile was converted to the numerical vectors to represent positive or negative instances. When SVM training, We took advantage of multiple SVMs because of the unbalanced training sets. Representative negative instances were drawn multiple times, and generated new traing sets with the same positive instances in the original traing set. When testing, the final decisions were made by the votes of those multiple SVMs. Generally, RBF kernel was used for the SVMs, and several parameters such as gamma and cost factor were tested. Our approach achieved more than 90% specificity throughout the protein kinase families, while the sensitivities recorded 60% on average.

• Nuclear Engineering and Technology
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• 제35권6호
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• pp.581-595
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• 2003

Transport lattice codes require the resonance integral tables for the resonant nuclides where the resonance integral is a function of the background cross section and can be prepared through a special program solving the slowing down equation. In case the cross section libraries do not include the resonance integral table for the resonant nuclides, the computational prediction produces a large error. We devised a new method using a Monte Carlo calculation for the effective resonance cross sections to solve this problem provisionally. We extended this method to obtain the resonance integral table for general purpose. The MCNP code is used for the effective resonance integrals and the LIBERTE code for the effective background cross sections. We modified the HELIOS library with the effective cross sections and the resonance integral tables obtained by the newly developed Monte Carlo method, and performed sample calculations using HELIOS and LIBERTE. The results showed that this method is very effective for the resonance treatment.

• 한국안전학회지
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• 제21권1호
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• pp.28-34
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• 2006

A procedure of estimating failure probability is demonstrated for a pressurized pipe of CrMo steel used at $538^{\circ}C$. Probabilistic fracture mechanics were employed considering variations of pressure loading, material properties and geometry. Probability density functions of major material variables were determined by statistical analyses of implemented data obtained by previous experiments. Distributions of the major variables were reflected in Monte Carlo simulation and failure probability as a function of operating time was determined. The creep crack growth life assessed by conventional deterministic approach was shown to be conservative compared with those obtained by probabilistic one. Sensitivity analysis for each input variable was also conducted to understand the most influencing variables to the residual life analysis. Internal pressure, creep crack growth coefficient and creep coefficient were more sensitive to failure probability than other variables.

• 한국건설관리학회논문집
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• 제6권1호
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• pp.73-79
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• 2005

This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

• 대한전기학회논문지:전력기술부문A
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• 제51권3호
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• pp.109-117
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• 2002

High accuracy of the load forecasting for power systems improves the security of the power system and generation cost. However, the forecasting problem is difficult to handle due to the nonlinear and the random-like behavior of system loads as well as weather conditions and variation of economical environments. So far. many studies on the problem have been made to improve the prediction accuracy using deterministic, stochastic, knowledge based and artificial neural net(ANN) method. In the conventional load forecasting method, the load forecasting maximum error occurred for the holidays on Saturday and Monday. In order to reduce the load forecasting error of the daily peak load for the holidays on Saturday and Monday, fuzzy concept and linear regression theory have been adopted into the load forecasting problem. The proposed algorithm shows its good accuracy that the average percentage errors are 2.11% in 1996 and 2.84% in 1997.