• Geomechanics and Engineering
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• v.15 no.4
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• pp.937-945
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• 2018

A probabilistic study of a reinforced earth wall in a frictional soil using the surface response methodology (RSM) is presented. A deterministic model based on numerical simulations is used (Abdelouhab et al. 2011, 2012b) and the serviceability limit state (SLS) is considered in the analysis. The model computes the maximum horizontal displacement of the wall. The response surface methodology is utilized for the assessment of the Hasofer-Lind reliability index and is optimized by the use of a genetic algorithm. The soil friction angle and the unit weight are considered as random variables while studying the SLS. The assumption of non-normal distribution for the random variables has an important effect on the reliability index for the practical range of values of the wall horizontal displacement.

• Journal of the Korean Society of Visualization
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• v.17 no.3
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• pp.66-69
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• 2019

An image compensating algorithm with high-vibration movement is proposed, using optical flow and the Kalman Filter. The temporal motion vector field is calculated by Optical flow and suspicious vectors are removed or adjusted by the Gaussian interpolation method. The high-vibrated vector filled is stabilized by the Kalman filter. Lastly, compensated images are obtained by affine transformation. This proposed algorithm gives good compensated video images on high-vibration situations.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.165-167
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• 2007

This paper presents a analysis method for power system stability using a Modified Genetic-based Power System Stabilized(MGPSS). The proposed MGPSS parameters are optimized using Modified Genetic Algorithm(MGA) in order to maintain optimal operation of generator under the various operating conditions. To improve the convergence characteristics, real variable string is adopted. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performance than conventional controller.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.799-804
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• 1993

In this paper, the scheme of combining the orbit correction and attitude control of a 3-axis stabilized satellite is suggested. Being coupled and complimentary, it is preferable to achieve the required orbit correction and the desired attitude control simultaneously. A solution of the probes simultaneous control of orbit correction and attitude of a satellite, is obtained by solving the two point boundary value problem numerically. The first-order gradient algorithm is used to solve the numerical problem. The simulation results show that the East-West station keeping process with the combined system of an orbit correction and an attitude control is satisfactory.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.56-66
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• 1993

In this paper, a fuzzy logic controll(FLC) is designed for the pointing loop of the spinstabilized platform. For the fuzzy inference, a fuzzy accelerator board using the Togai InfraLogic software and digital fuzzy processor(DFP110FC) is designed, and a validation of an algorithm for fuzzy logic control is also presented. Through the simulation and the experiment, it can be seen that the designed FLC shows better performance than a conventional controller using the same loop gain.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.405-409
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• 2008

Over 70% of the land is mountains in Korea, so that many roadways naturally includes tunnels. The air flow inside tunnel has complex characteristics, such that a new flow field is formed by following vehicles passing through the tunnel before previous flow field is stabilized. Due to these time delayed-transient characteristics, the ventilation facility requires the complex control algorithm that can handle adaptive and predictive controls. Also, it needs to be closely related to the disaster prevention system. The technology to integrate these system determines the success of TGMS. The pollutant levels exhausted from the vehicles passing through tunnel depend on vehicle years and passing velocity. They also depend on the slope and altitude of the tunnel. In order to solve this problem, an algorithm for estimating the compensating factors for calculating on design capacity of ventilation facilities was developed. Also, an integrated ventilation control algorithm with disaster prevention program to operate several tunnels was developed based on TGMS.

• Advances in Computational Design
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• v.2 no.3
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• pp.225-240
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• 2017

This paper presents the application of multiple linear regression (MLR) and artificial neural network (ANN) techniques for developing the models to predict the unconfined compressive strength (UCS) and Brazilian tensile strength (BTS) of the fiber reinforced cement stabilized fly ash mixes. UCS and BTS is a highly nonlinear function of its constituents, thereby, making its modeling and prediction a difficult task. To establish relationship between the independent and dependent variables, a computational technique like ANN is employed which provides an efficient and easy approach to model the complex and nonlinear relationship. The data generated in the laboratory through systematic experimental programme for evaluating UCS and BTS of fiber reinforced cement fly ash mixes with respect to 7, 14 and 28 days' curing is used for development of the MLR and ANN model. The data used in the models is arranged in the format of four input parameters that cover the contents of cement and fibers along with maximum dry density (MDD) and optimum moisture contents (OMC), respectively and one dependent variable as unconfined compressive as well as Brazilian tensile strength. ANN models are trained and tested for various combinations of input and output data sets. Performance of networks is checked with the statistical error criteria of correlation coefficient (R), mean square error (MSE) and mean absolute error (MAE). It is observed that the ANN model predicts both, the unconfined compressive and Brazilian tensile, strength quite well in the form of R, RMSE and MAE. This study shows that as an alternative to classical modeling techniques, ANN approach can be used accurately for predicting the unconfined compressive strength and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes.

• Journal of IKEEE
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• v.16 no.4
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• pp.328-334
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• 2012

In this paper, we analyzed the electromagnetic characteristics of the spherical frequency selective surface with different arrangement of crossed dipole slot elements for reducing the RCS(radar cross section). The three dimensional MOM(method of moment) with RWG basis is used to analyze the proposed structure. To reduce the simulation time, we applied the BiCGSTab(Biconjugate Gradient Stabilized) algorithm as an iterative method and presented the comparison results with Mie's theoretical results for PEC sphere to show the validity of this paper. From the simulation results, the different arrangement of elements array showed the difference RCS that cannot be negligible. The arrangement method of element in frequency selective surface will be one of variables for the design of curved frequency selective structures.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1804-1809
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• 2003

In a large-scale chemical plant, there are scheduling problems in inventory and packing process although production process is stabilized. The profit of the plant is restricted by these problems. In order to improve these problems, integrated scheduling model, which is concerned with whole processes from production to shipment, has been developed in this paper. In this model, decision variables are production sequence, silo allocation, amounts of bulk shipment and packing amounts. In case of a real plant, it is hard to solve by deterministic methods because there are too many decision variables to solve. In this paper, genetic algorithm is presented to solve a PVC process scheduling model within an hour with PCs.