• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1703_1704
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• 2009

Fuzzy neural ship controllers is used in ship steering control. It can make full use of the advantage of all kinds of intelligent algorithms. This provides an efficient way for this paper. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors. Utilizing the designed network to substitute the conventional fuzzy inference, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The ship control quality is effectively improved in case of appending additional sea state disturbance. The performance of controller is evaluated by the system simulation using simulink tools.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.76-86
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• 2002

In this paper, we suggest a hybrid genetic algorithm reinforced by a fuzzy logic controller (flc-HGA) to overcome weaknesses of conventional genetic algorithms: the problem of parameter fine-tuning, the lack of local search ability, and the convergence speed in searching process. In the proposed flc-HGA, a fuzzy logic controller is used to adaptively regulate the fine-tuning structure of genetic algorithm (GA) parameters and a local search technique is applied to find a better solution in GA loop. In numerical examples, we apply the proposed algorithm to a simple test problem and two complex combinatorial optimization problems. Experiment results show that the proposed algorithm outperforms conventional GAs and heuristics.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.933-938
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• 2007

These days, up-to-date humanoid robots are continuously developed. Among them, Qrio, Asimo[1,2] are famous for its unique walking technology and natural movement. These robots could show manufacturers' technological improvement and leave a good impression to the customer. In accordance with global trends, Samsung is also producing humanoid robot. The humanoid robot, however, could walk like a human compared to the industrial robot fixed in the factory. This feature could cause another dynamic effect while walking. In this paper, the robot's feet were examined to find out parameters that affect stability of the humanoid robot's feet. With the sensitivity analysis, the optimization procedure in design of experiments finds the most suitable performance of robot. Maximum deflection of the frame upon various cases was minimized, and rubber coefficients for shock absorption were optimized.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.599-604
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• 2002

Substructures position is considered as design parameter to obtain optimal structural changes to raise its dynamic characteristics. In conventional SDM (structural dynamics modification) method, the layout of modifying substructures position is first fixed and at that condition the structural optimization is performed by using the substructures size and/or material property as design parameters. But in this paper as a design variable substructures global translational and rotational position is treated. For effective structural modification the eigenvalue sensitivity with respect to that design parameter is derived based on measured frequency response function. The optimal structural modification is calculated by combining eigenvalue sensitivities and eigenvalue reanalysis technique iteratively. Numerical examples are presented to the case of beam stiffener optimization to raise the natural frequency of plate.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.594-597
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• 2007

The notebook system use the radial fan to cool the main chipsets which generate heat. It needs to improve cooling performance by increasing fan RPM or increasing fan volume. But the former accompanies acoustic noise problem and the latter has a limitation due to notebook height and cooling area. So this study shows fatal parameters in the fan performance view point, and optimization process with Design Of Experiment. With this result, the fan CFM increases with same size of fan and we can use it as a result of decreasing fan acoustic noise.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.3
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• pp.250-260
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• 2004

This study considers a linear connected-(r,s)-out-of-(m,n):F lattice system whose components are ordered like the elements of a linear (m,n )-matrix. We assume that all components are in the state 1 (operating) or 0 (failed) and identical and s-independent. The system fails whenever at least one connected (r,s)-submatrix of failed components occurs. The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unit time. To find the optimal threshold of maintenance intervention, we use a genetic algorithm for the cost optimization procedure. The expected cost per unit time is obtained by Monte Carlo simulation. The sensitivity analysis to the different cost parameters has also been made.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1586-1592
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• 2017

Voltage sourced converter (VSC) based direct-current (DC) grid has the ability to control power flow flexibly and securely, thus it has become one of the most valid approaches in aspect of large-scale renewable power generation, oceanic island power supply and new urban grid construction. To solve the optimal power flow (OPF) problem in DC grid, an adaptive particle swarm optimization (PSO) algorithm based on fuzzy control theory is proposed in this paper, and the optimal operation considering both power loss and voltage quality is realized. Firstly, the fuzzy membership curve is used to transform two objectives into one, the fitness value of latest step is introduced as input of fuzzy controller to adjust the controlling parameters of PSO dynamically. The proposed strategy was applied in solving the power flow issue in six terminals DC grid model, and corresponding results are presented to verify the effectiveness and feasibility of proposed algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.61-83
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• 2009

This study developed a variable demand traffic assignment model by stable dynamics. Stable dynamics, suggested by Nesterov and do Palma[19], is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with the user equilibrium model, which is based on the arc travel time function in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on congestion. It is therefore expected to be a useful analysis tool for transportation planners. In this study, we generalize the stable dynamics into the model with variable demands. We suggest a three stage optimization model. In the first stage, we introduce critical travel times and dummy links and determine variable demands and link flows by applying an optimization problem to an extended network with the dummy links. Then we determine link travel times and path flows in the following stages. We present a numerical example of the application of the model to a given network.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.284-290
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• 1993

In order to improve the adaptability of rice transplanter to seeding with different length when transplanting multicropping rice in south China. The seedling separating planting mechanism is resynthesized in the paper. According to the agronomy requirements of seedling's transplanting, optimum motional path of the tip point of planting needle is obtained. by applying the established kinematic model of the separating planting mechanism, the relevant software is compiled. On the basis of the features of the problem, the constrained optimization method is utilized to solve the problem with 24 restrictions. Thus, the optimum structure parameters are obtained to satisfy the path points accurately.