• KIEAE Journal
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• v.15 no.3
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• pp.29-36
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• 2015

Purpose: This study is as only basic research for the model Development of the New-Hanok Type Service Facilities in Apartment Housing, which is as a decisive factor used as a planning element for developing the model inherited tradition, There aimed at extracting the genetic factor of Korea's traditional architecture. Method: For this purpose, Consider the concept and regulations of the New-Hanok Type Service Facilities in Apartment Housing and examined the Domestic Application Status of the New-Hanok Type Service Facilities in Apartment Housing. It sets direction of the New-Hanok Type models development based on Expert advice and the literature, and was reviewed a primal reason system of Korea as an extraction base of genetic factors. Result: Then Through the framework of the vertical axis (the form), the horizontal axis (space), It extracted the genetic factors of the Korea Traditional Architecture, classified the genetic factors extracted as the structure(layout, construction, space), features, traditional beauty, investigated the content of the form representation and spatial meaning, and were characterized. Based on the result, It were comprehensive the genetic factors extracted as plan Elements for inheriting of the traditions.

• Architectural research
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• v.8 no.2
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• pp.43-48
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• 2006

The appropriate fleet estimation of the excavation equipment is a major factor in the determination of the cost and time requirements of a project. But the decision of what kind of equipment selected is often based on heuristic methods or trial and error in Korea. Thus, this study proposes a prototype model that uses genetic algorithms to select fleet estimation of loaders (backhoe) and trucks used in excavation work. To verify the applicability of this model, the case study was performed. And the result of the genetic model was compared with that of the trial & error method. The use of the genetic model suggested this study required 44days, 2 units of backhoes, 7 units of trucks, and a total cost of 171,839,756 won. With the estimated fleet number of equipment, the minimum cost of excavation work can be calculated, taking account of the time-cost trade-off. By utilizing this prototype model, the efficiency of excavation work can be improved.

• Architectural research
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• v.4 no.1
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• pp.33-38
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• 2002

The objective of this study is the development of discrete optimum design algorithms which is based on the genetic algorithms. The developed algorithms was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses structures and the constraints are stresses and displacements. This study solves the problem by introducing the genetic algorithms. The genetic algorithms consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed discrete optimum design algorithms was verified by applying the algorithms to optimum design examples.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.44 no.1
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• pp.57-67
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• 2008

Recently, Korean shipbuilding industry is keeping up the position of world wide No. 1 in world shipbuilding market share. It is caused by endless efforts to develope new technologies and methods and fast development of IT technologies in Korea, to raise up its productivities and efficiency in shipbuilding industry with many kinds of optimizing methods including genetic algorithm or artificial life algorithm... etc. In this paper, we have suggested the artificial life algorithm with relay search micro genetic algorithm. and we have improved a defect of simple genetic algorithm for its slow convergence speed and added a variety of solution candidates with applying relay search simple genetic algorithm. Finally, we have developed intelligent agent system for ship CAE modeling. We have tried to offer some conveniences a ship engineer for repeated ship CAE modeling by changing ship design repeatedly and to increase its accuracy of a ship model with it.

• Journal of Ship and Ocean Technology
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• v.11 no.4
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• pp.21-28
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• 2007

Recently the importance of the utilization of engineering data is gradually increasing. Engineering data contains the experiences and know-how of experts. Data mining technique is useful to extract knowledge or information from the accumulated existing data. This paper deals with generating optimal polynomials using genetic programming (GP) as the module of Data Mining system. Low order Taylor series are used to approximate the polynomial easily as a nonlinear function to fit the accumulated data. The overfitting problem is unavoidable because in real applications, the size of learning samples is minimal. This problem can be handled with the extended data set and function node stabilization method. The Data Mining system for the ship design based on polynomial genetic programming is presented.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.22-26
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• 2003

This paper presents a genetic algorithm based autonomic movement algorithm for an autonomous underwater vehicle(AUV) and verified it to simulation. Also, developed program that can do simulation on two dimension and three dimension in seabed environment. The presented algorithm is applicable to a escape from the recursive search and a development of obstacle avoidance system.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.114-116
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• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.1-7
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• 2015

The weight estimation of floating offshore structures such as FPSO, TLP, semi-Submersibles, Floating Offshore Wind Turbines etc. in the preliminary design, is one of direct measures of both construction cost and basic performance. Through both literature investigation and internet search, the weight data of floating offshore structures such as FPSO and TLP was collected. In this study, the weight estimation model with the genetic programming was suggested for FPSO. The weight estimation model using genetic programming was established by fixing the independent variables based on this data. In addition, the correlation analysis was performed to make up for the weak points of genetic programming; it is apt to induce over-fitting when the number of data is relatively smaller than that of independent variables. That is, by reducing the number of variables through the analysis of the correlation between the independent variables, the increasing effect in the number of weight data can be expected. The reliability of the developed weight estimation model was within 2% of error rate.

• Journal of Ship and Ocean Technology
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• v.9 no.4
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• pp.35-46
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• 2005

The performance of optimisation methods, based on penalty functions, is highly problem- dependent and many methods require additional tuning of some variables. This additional tuning is the influences of penalty coefficient, which depend strongly on the degree of constraint violation. Moreover, Binary-coded Genetic Algorithm (BGA) meets certain difficulties when dealing with continuous and/or discrete search spaces with large dimensions. With the above reasons, Real-coded Micro-Genetic Algorithm (R$\mu$GA) is proposed to find the global optimum of continuous and/or discrete nonlinear constrained engineering problems without handling any of penalty functions. R$\mu$GA can help in avoiding the premature convergence and search for global solution-spaces, because of its wide spread applicability, global perspective and inherent parallelism. The proposed R$\mu$GA approach has been demonstrated by solving three different engineering design problems. From the simulation results, it has been concluded that R$\mu$GA is an effective global optimisation tool for solving continuous and/or discrete nonlinear constrained real­world optimisation problems.

• Genomics & Informatics
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• v.13 no.2
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• pp.40-44
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• 2015

DNA microarray and next-generation sequencing provide data that can be used for the genetic analysis of multiple quantitative traits such as gene expression levels, transcription factor binding profiles, and epigenetic signatures. In particular, chromatin opening is tightly coupled with gene transcription. To understand how these two processes are genetically regulated and associated with each other, we examined the changes of chromatin accessibility and gene expression in response to genetic variation by means of quantitative trait loci mapping. Regulatory patterns commonly observed in yeast and human across different technical platforms and experimental designs suggest a higher genetic complexity of transcription regulation in contrast to a more robust genetic architecture of chromatin regulation.