• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.53-68
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• 1999

To improve the slow convergence property of the steepest ascent type algorithm for continuous D-optimal design problems. we develop a new algorithm. We apply the nonlinear system of equations as the necessary condition of optimality and develop the two-point algorithm that solves the problem of clustering. Because of the nature of the steepest coordinate ascent algorithm avoiding the problem of clustering itself helps the improvement of convergence speed. The numerical examples show the performances of the new method is better than those of various steepest ascent algorithms.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.622-624
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• 2005

This paper proposes a time series prediction method for the nonllinear system using the fuzzy system and its genetic algorithm, At first, we obtain the optimal fuzzy membership function using the genetic algorithm. With the optimal fuzzy rules and its input differences, a better time prediction series system may be obtained. We obtain a good result for the time prediction of the electric load.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.468-471
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• 2003

The A＊ algorithm is usually used in game programming, mainly because it is fast in finding a optimal path to goal. In this paper. This algorithm was utilized for path finding, HIMM(Histogramic In-Motion Mapping) method is used in map-building. Map is updated continuously with range data sampled by PSD sensors From the map, A＊ algorithm finds a optimal path and sends subsequently the most suitable point to the Eyebot. A＊ algorithm has been tested on the Eyebot in various unknown maps of unknown and proved to work well. It could escape the local minimum, also.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.24-27
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• 2002

The optimal designs of groundwater problems of contaminant containment and cleanup using linear programming and genetic algorithm are provided. In the containment problem, genetic algorithm shows the superior feature to linear programming. In cleanup problem, genetic algorithm makes reasonable optimal design. Un this study, it is demonstrated through numerical experiments that genetic algorithm can be applied to remedial designs of groundwater problems.

• Korean Journal of Remote Sensing
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• v.18 no.5
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• pp.291-297
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• 2002

Optimal allocation of viewers on a terrain in such a wav that the hidden area would be minimized has many practical applications. However, it is impossible in practical sense to evaluate all the possible allocations. In this paper, we propose an optimal allocation of viewers based on genetic algorithm that enables probabilistic search of huge solution space. An experiment for one and three viewers was performed. The algorithm converges to good solutions. Especially, in one viewer case, the algorithm found the best solution.

• Journal of Ocean Engineering and Technology
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• v.20 no.1 s.68
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• pp.69-76
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• 2006

The design of efficient search path to maximize the Cumulative Detection Probability(CDP) is mainly dependent on experience and intuition when searcher detect the target using SONAR in the ocean. Recently with the advance of modeling and simulation method, it has been possible to access the optimization problems more systematically. In this paper, a method for the optimal search path calculation is developed based on the combination of the genetic algorithm and the calculation algorithm for detection range. We consider the discrete system for search path, space, and time, and use the movement direction of the SONAR for the gene of the genetic algorithm. The developed algorithm, OASPP(Optimal Acoustic Search Path Planning), is shown to be effective, via a simulation, finding the optimal search path for the case when the intuitive solution exists. Also, OASPP is compared with other algorithms for the measure of efficiency to maximize CDP.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.10
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• pp.47-58
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• 2011

This paper proposes the optimal current detect(OCD) maximum power point tracking(MPPT) control of photovoltaic(PV) system for robust with environment changing. The output characteristics of the solar cell is a nonlinear and affected by a temperature, the solar radiation and temperature. Conventional MPPT control methods are tracked the maximum power point by constant incremental value. So these methods are slow the response speed and generated the vibration in steady state and cannot track the MPP in environment condition changing. And power loss is generated because of the self-excitation vibration in MPP region. To solve this problem, this paper proposes the novel control algorithm. Proposed algorithm is detected the optimal current in two control region using the output power and current curve. Detected current is used the converter switching for tracking the MPP. Proposed algorithm is compared output power error to conventional algorithm with radiation and temperature changing. In addition, the validity of the algorithm is proved through the output error response characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1089-1095
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• 2004

The genetic algorithms have been used to take a near optimal solution because The generation of the optimal Steiner tree from a given network is NP-hard problem,. The chromosomes in genetic algorithm are represented with the floating point representation instead of the existing binary string for solving this problem. A spanning tree was obtained from a given network using Prim's algorithm. Then, the new Steiner point was computed using genetic algorithm with the chromosomes in the floating point representation, and it was added to the tree for approaching the result. After repeating these evolving steps, the near optimal Steiner tree was obtained. Using this method, the tree is quickly and exactly approached to the near optimal Steiner tree compared with the existing genetic algorithms using binary string.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.36-43
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• 1999

This paper proposes a new hybrid genetic algorithm for auto-tuning fuzzy controllers improving the performance. In general, fuzzy controllers use pre-determined moderate membership functions, fuzzy rules, and scaling factors, by trial and error. The presented algorithm estimates automatically the optimal values of membership functions, fuzzy rules, and scaling factors for fuzzy controllers, using a hybrid genetic algorithm. The object of the proposed algorithm is to promote search efficiency by the hybrid optimization technique. The proposed hybrid genetic algorithm is based on both the standard genetic algorithm and a modified gradient method. If a maximum point is not be changed around an optimal value at the end of performance during given generation, the hybrid genetic algorithm searches for an optimal value using the the initial value which has maximum point by converting the genetic algorithms into the MGM(Modified Gradient Method) algorithms that reduced the number of variables. Using this algorithm is not only that the computing time is faster than genetic algorithm as reducing the number of variables, but also that can overcome the disadvantage of genetic algoritms. Simulation results verify the validity of the presented method.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.38-46
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• 1999

One of the tasks of maritime navigation is to decide upon the optimal navigation route that minimizes a vessals travel time and fuel consumption. Recently. ECDIS(Electronic Chart Display Information System) is used to decide the optimal navigation route and have expert knowledge of maritime navigation. In this paper, the system use $A^*$algorithm for optimal navigation route on ECDIS. But some problems is discovered in this situation. it requires many memory device and searching time. So this paper has tried to develope a advanced algorithm system that decides the optimal navigation route.