• 대한기계학회논문집A
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• 제30권6호
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• pp.698-704
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• 2006

This paper presents an electrode shape design method for the multi-mode sensors that could deteict the selected structural multiple modes. The structure used for this study is an isotropic cantilever beam type with a PVDF (polyvinylidene fluoride) which is bonded onto the structure as a sensor. The shape optimization problem is solved by using Genetic Algorithm (GA) with an appropriate objective function. The performance of analytical optimal shape sensor is compared with that of experimental work. The results show that the, obtained electrode shape sensors have good performance to detect the multiple vibration modes simultaneously.

• Steel and Composite Structures
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• 제7권6호
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• pp.421-440
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• 2007

An optimal design method in cooperated with nonlinear inelastic analysis is presented. The proposed nonlinear inelastic method overcomes the difficulties due to incompatibility between the elastic global analysis and the limit state member design in the conventional LRFD method. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are load-carrying capacity, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

• 대한기계학회논문집A
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• 제27권4호
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• pp.499-506
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• 2003

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several sub design structure matrices (DSMs) and processing them in parallel This paper proposes a new method for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multi-objective genetic algorithm and two sample test cases are presented to show the effect of the suggested decomposition method.

• 한국소음진동공학회논문집
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• 제17권1호
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• pp.80-87
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• 2007

In this paper, a method for identifying the location and extent of a damage in a structure using residual forces was presented. Element stiffness matrix reduction parameters in a finite element model were used to describe the damaged structure mathematically. The element stiffness matrix reduction parameters were determined by minimizing a global error derived from dynamic residual vectors, which were obtained by introducing a simulated experimental data into the eigenvalue problem. Genetic algorithm was used to get the solution set of element stiffness reduction parameters. The proposed scheme was verified using Euler-Bernoulli beam. The results were presented in the form of tables and charts.

• Genomics & Informatics
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• 제10권3호
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• pp.133-144
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• 2012

Genetic admixture in human, the result of inter-marriage among people from different well-differentiated populations, has been extensively studied in the New World, where European colonization brought contact between peoples of Europe, Africa, and Asia and the Amerindian populations. In Asia, genetic admixing has been also prevalent among previously separated human populations. However, studies on admixed populations in Asia have been largely underrepresented in similar efforts in the New World. Here, I will provide an overview of population genomic studies that have been published to date on human admixture in Asia, focusing on population structure and population history.

• 산업경영시스템학회지
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• 제32권2호
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• pp.158-170
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• 2009

This paper considers how the optimal export level is influenced by export risk, the degree of risk-averseness for exporting firms, and those firms' cost structure. In addition, export insurance is incorporated into some simple theoretical model to analyze the optimal export level. This paper applies genetic algorithm simulation to show that the exporting firms'risk-averseness do not affect the optimal export decision while export risk and cost function characteristic have relatively more significant effects on the optimal export level. Finally, our findings suggest that the most influential factor for the optimal export levels seems to be the monopoly power of exporting firms.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 가을 학술발표회 논문집
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• pp.145-152
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• 2003

An optimal design method in cooperated with nonlinear inelastic analysis method is presented. The proposed nonlinear inelastic method overcomes the difficulties due to incompatibility between the elastic global analysis and the limit state member design in the conventional LRFD method. The genetic algorithm uses a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used among sections in the database to look for high performance ones. They satisfy the constraint functions and give the lightest weight to the structure. The objective function is set to the total weight of the steel structure and the constraint functions are load-carrying capacities, serviceability, and ductility requirement. Case studies of a three-dimensional frame and a three-dimensional steel arch bridge are presented.

• Structural Engineering and Mechanics
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• 제17권5호
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• pp.707-725
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• 2004

An optimal design method with nonlinear elastic analysis is presented. The proposed nonlinear elastic method overcomes the drawback of the conventional LRFD method that accounts for nonlinear effect by using the moment amplification factors of $B_1$ and $B_2$. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are employed to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are strength, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.157-163
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• 2000

In this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algoithm(RVEGA) was presented for stabilization of an Inverter Pendulum(IP) system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the determinations of input or output neuron, the deleted neuron and the activation functions types are given according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. Through the simulations, we showed that the finally acquired optimal ENNC was successfully applied to the stabilization control of an IP system.

• 한국국방경영분석학회지
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• 제26권1호
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• pp.56-69
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• 2000

A frequency assignment problem on time division duplex system is considered. Republic of Korea Army (ROKA) has been establishing an infrastructure of tactical communication (SPIDER) system for next generation and it will be a core network structure of system. VHF system is the backbone network of SPIDER, that performs transmission of data such as voice, text and images. So, it is a significant problem finding the frequency assignment with no interference under very restricted resource environment. With a given arbitrary configuration of communications network, we find a feasible solution that guarantees communication without interference between sites and relay stations. We formulate a frequency assignment problem as an Integer Programming model, which has NP-hard complexity. To find the assignment results within a reasonable time, we take a genetic algorithm approach which represents the solution structure with available frequency order, and develop a genetic operation strategies. Computational result shows that the network configuration of SPIDER can be solved efficiently within a very short time.