• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.701-710
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• 2002

The framework, described in this paper, involves artificial evolutionary systems that re -produce aimed solutions through a simulated Darwinian evolution process. Through this process the framework designs structures of machines innovatively and emergently especially in the stages of conceptual and basic design. Since the framework simulates the evolution of nature, it inevitably involves processes that converse the natural evolution to the artificial evolution. For the conversion, based on several methods as the building block modeling, Artificial Life, evolutionary computation and the law of natural selection, we propose a series of processes that consists of modeling, evaluation, selection, evolution etc. We have demonstrated the implementation of the framework with the design of multi-step gear systems.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.221-224
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• 2009

In this paper, we deal with the development of an optimal design program for a dual-band of 0.92 GHz and 2.45 GHz with shorting pin and slot by using evolution strategy. the optimal shorting pin, coaxial feed and H-shaped patch are determined by using an optimal design program based on the evolution strategy. To achieve this, an interface program between a commercial EM analysis tool and the optimal design program is constructed for implementing the evolution strategy technique that seeks a global optimum of the objective function through the iterative design process consisting of variation and reproduction. The resonance frequencies of the dual-band antenna yielded by the optimal design program are 0.92 GHz and 2.45 GHz that show a good agreement to the design target values.

• Proceedings of the Korea Society of Design Studies Conference
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• 2002.05b
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• pp.18-19
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• 2002

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.68-69
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• 2004

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1355-1360
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• 2005

In this paper, we approach the problem of image filter design automation using a kind of intrinsic evolvable hardware architecture. For the purpose of implementing the intrinsic evolution process in a common FPGA chip and evolving a complicated digital circuit system-image filter, the design automation system employs the reconfigurable circuit architecture as the reconfigurable component of the EHW. The reconfigurable circuit architecture is inspired by the Cartesian Genetic Programming and the functional level evolution. To increase the speed of the hardware evolution, the whole evolvable hardware system which consists of evolution algorithm unit, fitness value calculation unit and reconfigurable unit are implemented by a commercial FPGA chip. The Celoxica RC1000 card which is fitted with a Xilinx Virtex xcv2000E FPGA chip is employed as the experiment platform. As the result, we conclude the terms of the synthesis report of the image filter design automation system and hardware evolution speed in the Celoxica RC1000 card. The evolved image filter is also compared with the conventional image filter form the point of filtered image quality.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.108-109
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• 2004

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.768-773
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• 2010

In this paper, we study on an optimal design of a triple-band PIFA (Planar Inverted-F Antenna) of 433 MHz, 912 MHz and 2.45 GHz by using evolution strategy. Generally, the resonant frequency of the PIFA is determined by the width and length of a U-type slot used. However the resonant frequencies of the multiple U slots are varied by the mutual effect of the slots. Thus the optimal width and length of U-type slots are determined by using an optimal design program based on the evolution strategy. To achieve this, an interface program between a commercial EM analysis tool and the optimal design program is constructed for implementing the evolution strategy technique that seeks a global optimum of the objective function through the iterative design process consisting of variation and reproduction. The resonant frequencies of initial model are 439.5 MHz, 981.5 MHz and 2.563 GHz. However, the resonant frequencies of the triple-band PIFA yielded by the optimal design program are 430.5 MHz, 907 MHz and 2.4515 GHz. Measured resonant frequencies are 433.5 MHz, 905.5 MHz and 2.454GHz, which show a good agreement with the simulation results.

• Archives of design research
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• v.14 no.4
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• pp.137-146
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• 2001

The purpose of the study is to explore and understand the product development through the theory of evolution. For the purpose of the study, an evolution mechanism was set up in which the products were applied with. The results showed three distinguishable types of product evolution 'the evolution of functions','the evolution of forms'and 'the evolution of symbols what the products represent'. In order to answer the research questions, , , , the research was carried out in three ways: firstly, some ideas of product evolution were looked closely through existing researches; secondly, the study explored the idea of evolution mechanism being a natural process like an organic system; finally by applying various products with the evolution mechanism, different patterns of product evolution were classified. The results of the study can be summarised as follows: ${\bullet}$ The evolution mechanism in this study can be defined as an 'organic system'that consists of the causes of evolution'(based on the needs and the willingness to have pleasure), 'the point of evolving'(based on a degree of imperfection) and 'the motive of evolution'(based on the readiness to make profit). ${\bullet}$ The evolution mechanism seems to suggest three different patterns in product evolution,'the evolution of functions', 'the evolution of forms' and 'the evolution of symbols'

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.130-131
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• 2004

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.399-404
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• 2012

Evolutionary algorithms such as genetic algorithm (GA) have been proven their effectiveness when applying to the design of fuzzy models. However, it tends to suffer from computationally expensWive due to the slow convergence speed. In this study, we propose an approach to develop fuzzy models by means of an improved differential evolution (IDE) to overcome this limitation. The improved differential evolution (IDE) is realized by means of an orthogonal approach and differential evolution. With the invoking orthogonal method, the IDE can search the solution space more efficiently. In the design of fuzzy models, we concern two mechanisms, namely structure identification and parameter estimation. The structure identification is supported by the IDE and C-Means while the parameter estimation is realized via IDE and a standard least square error method. Experimental studies demonstrate that the proposed model leads to improved performance. The proposed model is also contrasted with the quality of some fuzzy models already reported in the literature.