• Journal of Communications and Networks
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• v.15 no.5
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• pp.486-495
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• 2013

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensionalGA structure is proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.143-148
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• 1999

Design optimization is performed to calculated the draw-bead force for satisfying the design re-quirements. For an analysis tool a rigid-plastic finite element method with modified membrane element is adopted. response surface methodology is utilized for constructing the approximation surface for the optimum searching of draw bead force in sheet metal forming process. the algorithm developed is ap-plied to a design of the draw bead forces in a deep drawing process. The results show that the design of process parameters is applicable in complex metal forming analysis. It is also noted that the present algo-rithm enhances the stable optimum solution with small times of optimization iteration.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1753-1762
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• 2000

An inverse method is presented to obtain material's flow properties by using small punch test. This procedure employs, as the objective function of inverse analysis, the balance of measured load-di splacement response and calculated one during deformation. In order to guarantee convergence to global minimum, simulated annealing method was adopted to optimize the current objective function. In addition, artificial neural network was used to predict the load-displacement response under given material parameters which is the most time consuming and limits applications of global optimization methods to these kinds of problems. By implementing the simulated annealing for optimization along with calculating load-displacement curve by neural network, material parameters were identified irrespective of initial values within very short time for simulated test data. We also tested the present method for error-containing experimental data and showed that the flow properties of material were well predicted.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.112-117
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• 2003

This paper deals with the problem of synthesis of the 3-dimensional Grasp Planning. In previous studies the genetic algorithm has been used to find optimal grasping points, but it had a limitation such as the determination time of grasping points was so long. To overcome this limitation we proposed a new algorithm which employs the Neural Network. In the Neural network we chose input parameters based on the shape of the object and output parameters resulted from optimization with the GA method. In this study the GRNN method is employed, it has been trained by the result value of optimization method and it has been tested by known object. The algorithm is verified by computer simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.660-664
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• 2014

A diesel forklift truck under 3-ton class has disadvantages in the vibration transmission path. Because the weight ratio of body structure to powertrain which is source of excitation force is lower th an a mid-class forklift. In addition, the torsional and bending vibration mode frequencies of body structure are within the engine excitation frequency range, then high idle vibration generated by resonance. In this paper vehicle body structure design and optimization technique considering idle vibration reduction are presented. Design sensitivity analysis is applied to search the sensitive of design parameters in body structure. The design parameters such as thickness and pillar cross section were optimized to increase the torsional and bending vibration mode frequencies.

• International Journal of Korean Welding Society
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• v.3 no.2
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• pp.15-23
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.6
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• pp.677-682
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• 2011

In this study, a simulation model developed for a hydraulic breaker is verified through comparison of simulation results to the experimental results. For performance optimization, the design parameters are selected based on the physical parameters of the equipment for ease of modification. Also a factorial experiment and regression analysis were conducted to observe the effect of each parameter on the performance of the hydraulic breaker. As a result, a method for optimizing the performance of a hydraulic breaker is proposed.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.739-742
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• 1997

This paper proposes the structure and parameter optimization technique of fuzzy neural networks using genetic algorithm. Fuzzy neural network has advantages of both the fuzzy inference system and neural network. The determination of the optimal parameters and structure of the fuzzy neural networks, however, requires special efforts. To solve these problems, we propose a new learning method for optimization of fuzzy neural networks using genetic algorithm. It can optimize the structure and parameters of the entire fuzzy neural network globally. Numerical example is provided to show the advantages of the proposed method.

• Journal of Magnetics
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• v.16 no.4
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• pp.379-385
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• 2011

This paper presents an optimal design of a direct-drive permanent magnet synchronous generator for a small-scale wind energy conversion system. An analytical model of a small-scale grid-connected wind energy conversion system is presented, and the effects of generator design parameters on the payback period of the system are investigated. An optimization procedure based on genetic algorithm method is then employed to optimize four design parameters of the generator for use in a region with relatively low wind-speed. The aim of optimization is minimizing the payback period of the initial investment on wind energy conversion systems for residential applications. This makes the use of these systems more economical and appealing. Finite element method is employed to evaluate the performance of the optimized generator. The results obtained from finite element analysis are close to those achieved by analytical model.

• Journal of Welding and Joining
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• v.20 no.5
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• pp.120-126
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• 2002

Ni-5%Al alloy powder is widely used as the bond coating powder to improve the adhesive strength between the substrate and coating. The important properties in the bond coating are the deposition efficiency and surface roughness. In this study, it was tried to optimize the plasma spray parameters to maximize the deposition efficiency and surface roughness. In the first step, spray current and hydrogen gas flow rate were optimized in order to increase the deposition efficiency. In the next step, the seven plasma spray variables were selected and optimized to improve both the deposition efficiency and surface roughness using the Taguchi experimental method. By these optimization, the deposition efficiency was improved from about 10 % at the frist time to 51.2 % by the optimization of spray current and hydrogen gas flow rate and finally to 65.2 % by the Taguchi experimental method. The average surface roughness was increased from about $12.9\mu\textrm{m}$ to $15.4\mu\textrm{m}$.