• Journal of Digital Convergence
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• v.14 no.4
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• pp.349-353
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• 2016

The studies on the human environment and ecosystem analysis is being actively researched. In recent years, The service of genome analysis has been offering the customized service to prevent the disease as reading an individual's genome information. The genome information by analyzing technology is being required accurate and fast analyses of ecosystem-dielectrics due to the spread of the disease, the use of genetically modified organism and the influx of exotic. In this paper the algorithm of K-Mean clustering for a new classification system was utilized. It will provide new dielectrics information as quickly and accurately for many biologists.

• Journal of Digital Convergence
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• v.13 no.3
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• pp.155-165
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• 2015

Bankruptcy prediction has been one of the important research topics in finance since 1960s. In Korea, it has gotten attention from researchers since IMF crisis in 1998. This study aims at proposing a novel model for better bankruptcy prediction by converging three techniques - support vector machine(SVM), fuzzy theory, and genetic algorithm(GA). Our convergence model is basically based on SVM, a classification algorithm enables to predict accurately and to avoid overfitting. It also incorporates fuzzy theory to extend the dimensions of the input variables, and GA to optimize the controlling parameters and feature subset selection. To validate the usefulness of the proposed model, we applied it to H Bank's non-external auditing companies' data. We also experimented six comparative models to validate the superiority of the proposed model. As a result, our model was found to show the best prediction accuracy among the models. Our study is expected to contribute to the relevant literature and practitioners on bankruptcy prediction.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.1-8
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• 2011

This article proposes a hybrid approach involved in determining the size of stormwater control facilities as part of a very large scale urban retrofit project. The objective of the proposed hybrid approach is to restore the pre-development hydrologic cycle. Firstly, an appropriate IETD is determined to isolate single storm events from the continuous rainfall record. Then, using the NRCS-CN method, direct runoff and infiltration volume are computed for every storm events. Long-term statistics of direct runoff and infiltration volume are analyzed in each case of pre-development, post development, post development with detention only, and post-development with the proposed hybrid approach. In order to preserve long-term statistics of direct runoff and infiltration volume in the case of pre-development, the size of detention and infiltration-based retention are estimated using the genetic algorithm. The result shows that the proposed hybrid approach is very useful for restoring statistics of natural direct runoff and infiltration volume.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.04a
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• pp.154-157
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• 2000

Distributed piezoelectric sensor and actuator system has been designed for the active vibration control of shell structure. PVDF is used for the materials of sensor/actuator. To prevent the adverse effect of spillover, distributed modal sensor/actuator system is established. Although shell structure is three-dimensional structure, the PVDF sensor/actuator system can be treated as two-dimensional Finite element programs are developed to consider curved structures having PVDF modal sensor/actuator. The nine-node Mindlin shell element with five nodal degree of freedoms is used for finite element discretization. The electrode patterns and lamination angle of PVDF sensor/actuator are optimized to design the modal sensor/actuator system Genetic algorithm is used for optimization. Sensor is designed to minimize the observation spillover, and actuator is designed to minimize the system energy of the control modes under a given initial condition. Modal sensor/actuator for the first and second modes of singly curved cantilevered shell structure are designed using mentioned methods. Discrete LQG method is used as a control law. Experimental demonstrations of the active vibration control with designed sensor/actuator system have been performed successfully.

• Journal of the Korean Geotechnical Society
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• v.25 no.8
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• pp.23-32
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• 2009

In this study, the reliable and simple analysis method was proposed to predict the settlement characteristic of composite ground in stage of design and construction of sand compaction pile (SCP). Model parameters could be obtained by the optimization process based on genetic algorithm. In order to examine the proposed method, laboratory consolidation tests on the settlement characteristic of SCP composite ground were performed for various replacement ratio of sand such as 0 (no replacement), 20, 36, and 56%. The proposed model showed very good agreements with measured data in the relation of void ratio-log scaled stress and time-compression far each replacement ratio.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.125-130
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• 2014

The competitiveness in today's global market forces many companies to develop families of products to provide enough variety for the marketplace. The challenge when designing a product family is in resolving the tradeoff between product commonality and distinctiveness. Simultaneously it is necessary to consider environmental performance to design a product family as well as to shorten lead-times, improve quality and reduce costs. This paper proposes a metaheuristic algorithm based redesign methodology for green product family considering environmental performance. The proposed method uses a genetic algorithm as metaheuristic algorithm and green product family index (GPFI) to support green product family design. In addition, it provides the redesign methodology such as product family level and component level. A case study used table lamps as an product family's example shows the verification and effectiveness of the proposed method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.947-951
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• 2005

The concept of group technology has been successfully applied to many production systems including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem which has been intensively studied over 40 years. We obtain a production schedule of several family products on a single facility where setup times and costs can be reduced by using the concept of group technology. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem (GT-ELSP). Numerical example shows that the developed heuristic and the hybrid genetic algorithm outperform the existing heuristics.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.501-507
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• 1997

Composite material has very excellent mechanical properties including tensile stress and specific strength. Especially impact loads may be expected in many of the engineering applications of it. The suitability of composite material for such applications is determined not only by the usual paramenters, but its impactor energy-absorbing properties. Composite material under impact load has poor mechanical behavior and so needs tailoring its structure. Genetic algorithms(GA) is probabilistic optimization technique by principle of natural genetics and natural selection and neural networks(NN) is useful for prediction operation on the basis of learned data. Therefore, This study presents optimization techniques on the basis of genetic algorithms and neural networks to minimum stiffness design of laminated composite material.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.729-737
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• 1996

Laminated composite plates have been applied to aircraft structures because their properties are superior to the conventional materials and the laminates have anisortropic elastic properties. However, it tis diffcult to determine stacking structures using actual design variables for the lack of searching capability of existing optimization technique. GA(generic algorithms) are robust search algorithms based on the mechanics of natural selection and natural genetics. Therefore, this study presents an application of IGA to stiffness and weight optimization design and gives the various stacking structures suitable to constraint conditions.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.2
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• pp.7-14
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• 2013

In this paper, the optimal design of composite rotor blade cross-section is performed using a genetic algorithm. Skin thickness, torsion box thickness and skin lay-up angle are adopted as discrete design variables. The position and width of a torsion box are considered as continuous variables. An object function of optimal design is to minimize the mass of a rotor blade, and constraints are failure index, center mass, natural frequency and blade minimum mass per unit length. Finally, design variables such as the thickness and lay-up angles of a skin, and the thickness, position and width of a torsion box are determined by using an in-house program developed for the optimal design of rotor blade cross-section.