• Journal of the Korean Data and Information Science Society
• /
• 제14권4호
• /
• pp.845-852
• /
• 2003

Forecasting exchange rate movements is a challenging task since exchange rates impact world economy and determine value of international investments. In particular, Korean-U.S. exchange rate behavior is very important because of strong Korean and U.S. trading relationship. Neural networks models have been used for short-term prediction of exchange rate movements. Least squares support vector machine (LS-SVM) is used widely in real-world regression tasks. This paper describes the use of LS-SVM for short-term and long-term prediction of Korean-U.S. exchange rate.

• 콘크리트학회논문집
• /
• 제12권4호
• /
• pp.69-78
• /
• 2000

Creep of concrete is the most dominating factor affecting time-dependent deformations of concrete structures. Especially, creep deformation for design and construction in prestressed concrete structures should be predicted accurately because of its close relation with the loss in prestree of prestressed concrete structures. Existing creep-prediction models for special applications contain several impractical factors such as the lack ok accuracy, the requirement of long-term test and the lack of versatility for change in material properties, ets., which should be improved. In order to improve those drawbacks, a methodology to modify the creep-prediction equation specified in current Korean concrete structures design standard (KCI-99), which underestimates creep of concrete and does not consider change of condition in mixture design, is proposed. In this study, short-term creep tests were carried out for early-age concrete within 28 days after loading and their test results on influencing factors in the equation are analysed. Then, the prediction equation was modified by using the early-age creep test results. The modified prediction equation was verified by comparing their results with results obtained from long-term creep test.

• 한국건설관리학회논문집
• /
• 제22권3호
• /
• pp.21-30
• /
• 2021

본 연구는 딥러닝의 반복적 예측방식을 활용하여 5개월의 철근 가격 예측방법을 제안한다. 이 방식은 입력데이터의 특성을 모두 단기예측하여 원 데이터에 추가하고, 추가된 데이터로 다음의 시점을 예측하는 과정을 반복하여 장기 예측한다. 본 연구에서 제시하는 방식으로 1개월에서 5개월까지 예측한 철근 가격의 예측 평균 정확도는 약 97.24%이다. 제안된 방식을 통해 인간의 경험과 판단을 통한 가격 추정방법의 체계성을 보완하여 기존의 방식보다 정확한 비용계획이 가능할 것으로 사료된다. 또 철근 이외의 건축재료를 비롯하여 시계열 데이터로 가격을 장기예측하는 연구에서 본 연구에서 제시한 방법이 활용될 수 있을 것으로 기대한다.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 1998년도 가을 학술발표논문집(II)
• /
• pp.462-467
• /
• 1998

A rational method for prediction of long-term deflections of reinforced concrete beams under sustained loads was proposed. Strain and stress distributions of uncracked and fully cracked sections after creep and shrinkage were determined from the requirements of strain compatibility and force equilibrium of a section, and then long-term deflections were calculated from the section analysis results. In fully cracked section analysis, noncoincidence of the neutral axis of strain and the neutral axis of stress after creep and shrinkage was taken into account. The accuracy of the proposed method was verified by comparison with several experimental measurements of beam deflections. The proposed approximate procedure gave the better predictions than the existing approximate methods. At the same time, the proposed method also retained simplicity of the calculation, since maximum long-term deflection could be obtained without tedious integration of the curvatures.

• Geomechanics and Engineering
• /
• 제36권1호
• /
• pp.83-97
• /
• 2024

It is important to make reasonable prediction about the long-term deformation of high rockfill geostructures. However, the deformation is usually underestimated using the rockfill parameters obtained from laboratory tests due to different size effects, which make it necessary to identify parameters from in-situ monitoring data. This paper proposes a novel hybrid back-analysis method with a modified objective function defined for the time-dependent back-analysis problem. The method consists of two stages. In the first stage, an improved weighted average method is proposed to quickly narrow the search region; while in the second stage, an adaptive response surface method is proposed to iteratively search for the satisfactory solution, with a technique that can adaptively consider the translation, contraction or expansion of the exploration region. The accuracy and computational efficiency of the proposed hybrid back-analysis method is demonstrated by back-analyzing the long-term deformation of two high embankments constructed for airport runways, with the rockfills being modeled by a rheological model considering the influence of stress states on the creep behavior.

• Steel and Composite Structures
• /
• 제30권6호
• /
• pp.535-550
• /
• 2019

Prestressed concrete (PC) bridges using corrugated steel webbing have emerged as one of the most promising forms of steel-concrete composite bridge. However, their long-term behavior is not well understood, especially in the case of large-span bridges. In order to study the time-dependent performance, a large three-span PC bridge with corrugated steel webbing was compared to a similar conventional PC bridge to examine their respective time-dependent characteristics. In addition, a three-dimensional finite element method with step-by-step time integration that takes into account cantilever construction procedures was used to predict long-term behaviors such as deflection, stress distribution and prestressing loss. These predictions were based upon four well-established empirical creep prediction models. PC bridges with a corrugated steel web were observed to have a better long-term performance relative to conventional PC bridges. In particular, it is noted that the pre-cambering for PC bridges with a corrugated steel web could be smaller than that of conventional PC bridges. The ratio of side-to-mid span has great influence on the long-term deformation of PC bridges with a corrugated steel web, and it is suggested that the design value should be between 0.4 and 0.6. However, the different creep prediction models still showed a weak homogeneity, thus, the further experimental research and the development of health monitoring systems are required to further progress our understanding of the long-term behavior of PC bridges with corrugated steel webbing.

• Journal of Positioning, Navigation, and Timing
• /
• 제8권4호
• /
• pp.209-214
• /
• 2019

Precise point positioning (PPP) requires precise orbit and clock products. International GNSS service (IGS) real-time service (RTS) data can be used in real-time for PPP, but it may not be possible to receive these corrections for a short time due to internet or hardware failure. In addition, the time required for IGS to combine RTS data from each analysis center results in a delay of about 30 seconds for the RTS data. Short-term orbit prediction can be possible because it includes the rate of correction, but the clock correction only provides bias. Thus, a short-term prediction model is needed to preidict RTS clock corrections. In this paper, we used a long short-term memory (LSTM) network to predict RTS clock correction for three minutes. The prediction accuracy of the LSTM was compared with that of the polynomial model. After applying the predicted clock corrections to the broadcast ephemeris, we performed PPP and analyzed the positioning accuracy. The LSTM network predicted the clock correction within 2 cm error, and the PPP accuracy is almost the same as received RTS data.

• 한국항행학회논문지
• /
• 제23권6호
• /
• pp.561-569
• /
• 2019

태양광 발전은 일사량만 있으면 전기에너지를 얻을 수 있기 때문에, 새로운 에너지 공급원으로 용도가 급증하고 있다. 본 논문은 실제 태양광 발전 시스템의 컨버터 출력을 이용하여 장단기 출력 예측을 하였다. 예측 알고리즘은 다중선형회귀와 머신러닝의 지도학습 중 분류모델인 서포트 벡터 머신 그리고 DNN과 LSTM 등 딥러닝을 이용하였다. 또한 기상요소의 입출력 구조에 따라 3개의 모델을 이용하였다. 장기 예측은 월별, 계절별, 연도별 예측을 하였으며, 단기 예측은 7일간의 예측을 하였다. 결과로서 RMSE 측도에 의한 예측 오차로 비교해 본 결과 다중선형회귀와 SVM 보다는 딥러닝 네트워크가 예측 정확도 측면에서 더 우수하였다. 또한, DNN 보다 시계열 예측에 우수한 모델인 LSTM이 예측 정확도 측면에서 우수하였다. 입출력 구조에 따른 실험 결과는 모델 1보다 모델 2가 오차가 적었으며, 모델 2보다는 모델 3이 오차가 적었다.

• Journal of information and communication convergence engineering
• /
• 제5권2호
• /
• pp.171-176
• /
• 2007

To give a guarantee a consistently high level of quality and reliability of Telematics traffic service, traffic flow forecasting is very important issue. In this paper, we proposed an adaptable integrated prediction model to predict the traffic flow in the future. Our model combines two methods, short-term prediction model and long-term prediction model with different combining coefficients to reflect current traffic condition. Short-term model uses the Kalman filtering technique to predict the future traffic conditions. And long-term model processes accumulated speed patterns which means the analysis results for all past speeds of each road by classifying the same day and the same time interval. Combining two models makes it possible to predict future traffic flow with higher accuracy over a longer time range. Many experiments showed our algorithm gives a better precise prediction than only an accumulated speed pattern that is used commonly. The result can be applied to the car navigation to support a dynamic shortest path. In addition, it can give users the travel information to avoid the traffic congestion areas.

• 한국재난관리표준학회지
• /
• 제1권3호
• /
• pp.51-57
• /
• 2008

프리스트레스트 콘크리트 사장교는 재료의 특성상 크리프 및 건조수축 등에 의한 장기거동의 영향을 크게 받는다. 이 연구에서는 콘크리트 구조물의 장기거동 예측에 일반적으로 이용되는 CEB-FIP모델과 ACI 모델을 예제 교량에 적용하여 상대습도의 변화에 따른 영향을 알아보았다. 주형 모멘트의 경우 CEB-FIP 모델이 ACI 모델보다 상대습도 변화에 대해 더 큰 영향을 받으며 영향도도 경우에 따라서는 무시할 수 없을 것으로 나타났다. 또한 동일 조건에서도 두 모델간 장기거동이 일부 단면에서는 비교적 크게 차이가 났다. 따라서, 장기거동에 대한 수치해석 결과는 재료시험과 예측모텔간의 영향 인자들에 대 한 민감도 분석을 거친 후에 보완하여 적용할 필요가 있다고 본다.