• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.398-398
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• 2015

To estimate and forecast runoff by using Aritifitial Neaural Networks model (ANNs). it has been studied in Thailand for the past 10 years. The model was developed in order to be conformed with the conditions in which the collected dataset is short and the amount of dataset is inadequate. Every year, the Northerpart of Thailand faces river overflow and flood inundation. The most important basin in this area is Yom basin. The purpose of this study is to forecast runoff at Y.14 gauge station (Si-Satchanalai district, Sukhothai province) for 3 days in advance. This station located at the upstream area of Yom River basin. Daily rainfall and daily runoff from Royal Irrigation Department and Meteorological Department during flood period 2000-2012 were used as input data. In order to check an accuracy of forecasting, forecasted runoff were compared with observed data by pursuing Nash Sutcliffe Efficiency (NSE) and Coefficient of Determination ($R^2$). The result of the first day gets the highest accuracy and then decreased in day 2 and day 3, consequently. NSE and $R^2$ values for frist day of runoff forecasting is 0.76 and 0.776, respectively. On the second day, those values are 0.61 and 0.65, respectively. For the third day, the aforementioned valves are 0.51 and 0.52, respectively. The results confirmed that the ANNs model can be used when the range of collected dataset is short and insufficient. In conclusion, the ANNs model is suitable for applying during flood incident because it is easy to use and does not require numerous parameters for simulating.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.

• Steel and Composite Structures
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• v.14 no.1
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• pp.1-20
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• 2013

This paper presents the formulation for a novel force-based 1-D compound-element that captures both material and second order P-${\Delta}$ nonlinearities in steel frames. At the nodal points, the element is attached to nonlinear rotational and a translational springs which represent the flexural and axial stiffness of the connections respectively. By decomposing the total strain in the material as well as the generalised displacements of the flexible connections to their elastic and inelastic components, a secant solution strategy based on a direct iterative scheme is introduced and the corresponding solution strategy is outlined. The strain and slope of the deformed element are assumed to be small; however the equilibrium equations are satisfied for the deformed element taking account of P-${\Delta}$ effects. The formulation accuracy and efficiency is verified by some numerical examples on the nonlinear static, cyclic and dynamic analysis of steel frames.

• Structural Engineering and Mechanics
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• v.20 no.6
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• pp.609-630
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• 2005

A reliability analysis method is proposed in this paper through a combination of the advantages of the response surface method (RSM), finite element method (FEM), first order reliability method (FORM) and the importance sampling updating method. The accuracy and efficiency of the method is demonstrated through several numerical examples. Then the method is used to estimate the serviceability reliability of cable-stayed bridges. Effects of geometric nonlinearity, randomness in loading, material, and geometry are considered. The example cable-stayed bridge is the Second Nanjing Bridge with a main span length of 628 m built in China. The results show that the cable sag that is part of the geometric nonlinearities of cable-stayed bridges has a major effect on the reliability of cable-stayed bridge. Finally, the most influential random variables on the reliability of cable-stayed bridges are identified by using a sensitivity analysis.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.133-140
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• 2000

The objective of this study is to develop a damage model based on damage mechanics that can be used to analyze the mechanical behavior of structures with defects and the global behavior of damaged structures. A modified second order damage tensor that can be applied to finite element analysis is used to reflect the effect of damage. The damage stress computed from the effective stress is considered as an additional loading term acting on nodes and can represent the effect of crack surface. The accuracy of the proposed algorithm is verified by comparing the analysis results with the experimental data from other studies and the analysis results based on transverse isotropic theory. The developed damage model is applied to the analyses of structures with cracks under linear elastic condition. Numerical results show that the developed model can effectively analyze the global behavior of damaged structures.

• Earthquakes and Structures
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• v.14 no.1
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• pp.45-53
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• 2018

A family of the structure-dependent methods seems very promising for time integration since it can simultaneously have desired numerical properties, such as unconditional stability, second-order accuracy, explicit formulation and numerical dissipation. However, an unusual overshoot, which is essentially different from that found by Goudreau and Taylor in the transient response, has been experienced in the steady-state response of a high frequency mode. The root cause of this unusual overshoot is analytically explored and then a remedy is successfully developed to eliminate it. As a result, an improved formulation of this family method can be achieved.

• Advances in aircraft and spacecraft science
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• v.5 no.4
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• pp.445-458
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• 2018

Turbulent airflow in channels of rectangular cross section with symmetric centerbodies is studied numerically. Shock wave configurations formed in the channel and in front of the entrance are examined. Solutions of the unsteady Reynolds-averaged Navier-Stokes equations are obtained with finite-volume solvers of second-order accuracy. The solutions demonstrate an expulsion/swallowing of the shocks with variations of the free-stream Mach number or angle of attack. Effects of the centerbody length and thickness on the shock wave stability and flow bifurcation are examined. Bands of the Mach number and angle of attack, in which there exist non-unique flow fields, are identified.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.10
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• pp.1458-1466
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• 2004

Deterministic optimum designs that are obtained without consideration of uncertainties could lead to unrealiable designs. Such deterministic engineering optimization tends to promote the structural system with less reliability redundancy than obtained with conventional design procedures using the factor of safety. Consequently, deterministic optimized structures will usually have higher failure probabilities than unoptimized structures. This paper proposes the reliability based design optimization technique fur apressure tank considering temperature effect. This paper presents an efficient and stable reliability based design optimization method by using the advanced first order second moment method, which evaluates a probabilistic constraint for more accuracy. In addition, the response surface method is utilized to approximate the performance functions describing the system characteristics in the reliability based design optimization procedure.

• 한국전산유체공학회:학술대회논문집
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• 2000.10a
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• pp.54-59
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• 2000

A numerical study of axisymmetric rocket main nozzle flow has been accomplished. The CSCM upwind flux difference splitting method with an iterative time marching scheme having second order accuracy in time and space has been used to simulate unsteady flow characteristics in an axisymmetric rocket main nozzle. Though the pressure vary at nozzle inlet with the lapse of time, Mach No. and the density were not changed significontly compared with the temperature. Specific heat ratio $\gamma$=1.134 predicted higher temperature at nozzle throat and exit and nondimensional thrust coefficients at exit than specific heat ratio $\gamma$=1.4 did.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.4
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• pp.811-825
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• 1998

An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.