• Proceedings of the Korean Geotechical Society Conference
• /
• 2001.03a
• /
• pp.379-386
• /
• 2001

Piled raft foundations are usually used to reduce total and differential settlements of superstructures. In the piled raft foundations, the raft is often on its own able to provide adequate bearing capacity and only few widely spaced piles are added to the foundation to keep settlements be1ow a certain limit. In this paper, experimental studies on the load sharing ratio between piles and raft are carried out. Also, for evaluating the application of optimum design technique using a genetic algorithm, optimal locations of files are compared with the results of laboratory model tests. from tile results of laboratory model tests, there are found that the load sharing ratio between files and raft is depended on the number of piles and stiffness of raft, and the optimal locations of piles became concentrated on the middle of rafts. From these results of laboratory model tests, the optimum technique using a genetic algorithm is acknowledged to the application in the piled raft.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.1 no.3
• /
• pp.109-117
• /
• 1993

A carbon/epoxy composite drive shaft used for the power transmission of the automobiles with steel joints. Compared with the metallic drive shaft, the composite one has the weight saving of 50% with equivalent torsional strength and fatigue characteristics. In this study, the filament winding technique for the composite tube and composite/metal joining technique are estabilished. The performance test of the drive shaft is carried out. The optimal condition of the surface roughness of the steel adherend was $1.5{{\mu}m}$ to $2.5{{\mu}m}$, and the optimal condition of the bonding thickness was 0.15mm. Maximum torque and torsional stiffness of the composite drive shaft manufactured by filament winding process were found to be $210kg{\cdot}m$ and $18.5kg{\cdot}m/deg$, respectively.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.30 no.1
• /
• pp.55-74
• /
• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.40 no.9
• /
• pp.929-936
• /
• 1991

An estimator for a discrete nonlinear system is derived in the sense of minimum mean square error. An optimal estimator for nonlinear system is very difficult to find and it will be infinite dimensional even if it is found. It has been known that the statistical linearization technique makes it possible to obtain a finite dimensional estimator. In this paper, the procedure of its derivation using the statistical linearization technique that gives an exact mean and variance information is introduced in the sense of minimum mean square error. The derived estimator cannot be clainmed to be globally optimal estimator because it uses the Gaussian assumption to the non-Gaussian distributed nonlinear output. However, the proposed filter exhibits a better performance compared to extended Kalman filter. Simulation results of a simple example present the improvement of the proposed filter in convergent property over the extended Kalman filter.

• Journal of Electrical Engineering and information Science
• /
• v.2 no.3
• /
• pp.51-60
• /
• 1997

A practically applicable collision free trajectory planning technique for tow robot systems is proposed. The robot trajectories considered in this work are composed of many segments, an at the intersection points between segments robots stop to assemble, weld, ordo other jobs by the attached a end-effectors. The proposed method is based on the Planning-Coordination Decomposition where planning is to find a trajectory of each robot independently according to their tasks and coordination is to find a velocity modification profile to avoid collision with each other. To fully utilize the independently planned trajectories and to ensure no geometrical path deviation after coordination, we develop a simple technique added the minimal delay time to avoid collision just before moving along path segments. We determine the least delay time by the graphical method in the Coordination space where collisions and coordinations are easily visualized. We classify all possible cases into 3 group and derive the optimal solution for each group.

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.1E
• /
• pp.66-69
• /
• 1998

Idle shake vibration characteristics of a vehicle are mainly influenced not only by the stiffnesses of the beam type structures such as pillars and rockers, but also by the stiffnesses of the joint structures, at which several beam structures are jointed together. In the early design stage of the car body structure a simple FE model has been used, in which joints are modeled as linear springs to represent the stiffnesses of the joint structures. In this paper a new modeling technique for the joint structure is presented using an equivalent beam, instead of using a spring. The modeling technique proposed is utilized to design optimal joint structures that meet the required vibration performance of the total vehicle structure.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.571-576
• /
• 2007

This study presents stiffness-based optimal design to control quantitatively lateral drift of frame-shear wall structures subject to seismic loads. To this end, lateral drift constraints are established by introducing approximation concept that preserves the generality of the mathematical programming and can efficiently solve large scale problems. Also, the relationships of sectional properties are established to reduce the number of design variables and resizing technique of member is developed under the 'constant-shape' assumption. Specifically, the methodology of dynamic displacement sensitivity analysis is developed to formulate the approximated lateral displacement constraints. The 12 story frame-shear wall structural models is considered to illustrate the features of dynamic stiffness-based optimal design technique proposed in this study.

• Journal of Advanced Marine Engineering and Technology
• /
• v.23 no.4
• /
• pp.480-487
• /
• 1999

In this paper we propose a neural network precompensated PID(NNP PID) controller for load frequency control of 2-area power system. While proportional integral derivative(PID) controllers are used in power system they have many problems because of high nonlinearities of the power system So a neural network-based precompensation scheme is adopted into a conventional PID controller to obtain a robust control to the nonlinearities. The applied neural network precompen-sator uses an error back-propagation learning algorithm having error and change of error as inputand considers the changing component of forward term of weighting factor for reducing of learning time. Simulation results show that the proposed control technique is superior to a conventional PID controller and an optimal controller in dynamic responses about load disturbances. The pro-posed technique can be easily implemented by adding a neural network precompensator to an existing PID controller.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.35 no.9
• /
• pp.403-408
• /
• 1986

In this paper, the method to improve the efficiency of an induction motor at light load is discussed. Efficiency of induction motor can be very substantially improved by keeping the slip frequency as constant. Therefore, to simplify the control loop, algorithm which maintain constant slip frequency and control the input voltage is adopted. Simplified high efficiency drive of induction motor using PLL technique is suggested. In order to verify the validity of this system, the test results are compared with those obtained by optimal slip drive system and then we found closer to the optimal efficiency. For example its efficiency is improved from 18[%] to 42[%] at a few fraction of the full load (20[%]).

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.20 no.3
• /
• pp.232-238
• /
• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.