• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.9-11
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• 1995

In this paper, tile squirrel case induction motors required multi-objective function are designed. As the objective function of the optimization program, we select the linear combination of loss and mass of motors by using weighting factors. Optimization process is performed by using the evolution strategy (ES). ES is the algorithm that can find the global minimum. To verify validity of the proposed method, a sample design is tried.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.21-23
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• 1997

The analysis of the permanent type synchronous motor is performed by using the finite element method (FEM). The optimal design of the permanent magnet is presented for minimizing cogging torque in this paper. The cogging torque is expressed in terms of scalar potential computed by the virtual work formula. The minimization of cogging torque is achieved by using the ( ${\mu}$ + ${\lambda}$ ) Evolution Strategy (ES) and the selected flux densities are used to a constraint.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.201-209
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• 2013

A new dynamic reliability analysis of structure under repeated random loads is proposed in this paper. The proposed method is developed based on the idea that the probability density of several times random loads can be derived from the probability density of single-time random load. The reliability prediction models of structure based on time responses under several times random loads with and without strength degradation are obtained by using the stress-strength interference theory and probability density evolution method. The resulting differential equations in the prediction models can be solved by using the forward finite difference method. Then, the probability density functions of strength redundancy of the structures can be obtained. Finally, the structural dynamic reliability can be calculated using integral method. The efficiency of the proposed method is demonstrated numerically through a speed reducer. The results have shown that the proposed method is practicable, feasible and gives reasonably accurate prediction.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.755-766
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• 2009

Software architecture allows us to make many decisions about a software system and analyze it even before it exists in order to make systematic and planned development possible. Similarly, architecture-based software evolution planningmakes planned evolution possible by allowing us to make many decisions about evolution of a software system and analyze its evolution at the level of architecture design before software evolution is realized. In this paper, we develop a framework for architecture-based software evolution planning for the class of deterministic evolution plans by defining and relating various essential concepts and developing its valuationmechanism so that a plan with the greatest value among candidate plans can be selected as an optimal plan. A case study is conducted for explicating the framework and exemplifying its usage.

• Advances in Computational Design
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• v.1 no.1
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• pp.79-86
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• 2016

In this study, the three different meta-heuristics namely the Grey Wolf Optimizer (GWO), Stochastic Fractal Search (SFS), and Adaptive Differential Evolution with Optional External Archive (JADE) algorithms are examined. This study considers optimization of the planer frame to minimize its weight subjected to the strength and displacement constraints as per the American Institute of Steel and Construction - Load and Resistance Factor Design (AISC-LRFD). The GWO algorithm is associated with grey wolves' activities in the social hierarchy. The SFS algorithm works on the natural phenomenon of growth. JADE on the other hand is a powerful self-adaptive version of a differential evolution algorithm. A one-bay ten-story planar steel frame problem is examined in the present work to investigate the design ability of the proposed algorithms. The frame design is produced by optimizing the W-shaped cross sections of beam and column members as per AISC-LRFD standard steel sections. The results of the algorithms are compared. In addition, these results are also mapped with other state-of-art algorithms.

• International Journal of High-Rise Buildings
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• v.5 no.3
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• pp.221-232
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• 2016

With the booming of construction and property industries in China, the demand for high-rises and mega-scale buildings with more integrated building functions, open- and tailor-shaped outlooks, better connections to municipal infrastructures, and higher grades of building importance has been increasing in the past two decades. The seismic design and engineering of such modern mega-buildings face engineering challenges such as hazard mitigation of extreme actions and surroundings, integrated structural frameworks and building skins, complex connections, and overall construction efficiency. It is the work of a new generation of civil and structural engineers to enhance engineering efficiency and achieve overall engineering, environmental, and economical effectiveness for these high-rise projects. This paper elaborates the above topics through case studies on the design and construction of four such developments in China. Some rethinking is conducted on evolution in modern seismic engineering and design through innovation to achieve an acceptable level of overall sustainability and building effectiveness.

• Journal of Magnetics
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• v.18 no.1
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• pp.65-73
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• 2013

In this paper, design and performance analysis of robust and inexpensive permanent magnet-assisted synchronous reluctance generators (PMa-SynRG) for tactical and commercial generator sets is studied. More specifically, the optimal design approach is investigated for minimizing volume and maximizing performance for the portable generator. In order to find optimized PMa-SynRG, stator winding configurations and rotor structures are analyzed using the lumped parameter model (LPM). After comparisons of stator windings and rotor structure by LPM, the selected stator winding and rotor structure are optimized using a differential evolution strategy (DES). Finally, output performances are verified by finite element analysis (FEA) and experimental tests. This design process is developed for the optimized design of PMa-SynRG to achieve minimum magnet and machine volume as well as maximum efficiency simultaneously.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.601-606
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• 1998

In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• Journal of Microbiology and Biotechnology
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• v.33 no.10
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• pp.1257-1267
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• 2023

Although rational genetic engineering is nowadays the favored method for microbial strain improvement, building up mutant libraries based on directed evolution for improvement is still in many cases the better option. In this regard, the demand for precise and efficient screening methods for mutants with high performance has stimulated the development of biosensor-based high-throughput screening strategies. Genetically encoded biosensors provide powerful tools to couple the desired phenotype to a detectable signal, such as fluorescence and growth rate. Herein, we review recent advances in engineering several classes of biosensors and their applications in directed evolution. Furthermore, we compare and discuss the screening advantages and limitations of two-component biosensors, transcription-factor-based biosensors, and RNA-based biosensors. Engineering these biosensors has focused mainly on modifying the expression level or structure of the biosensor components to optimize the dynamic range, specificity, and detection range. Finally, the applications of biosensors in the evolution of proteins, metabolic pathways, and genome-scale metabolic networks are described. This review provides potential guidance in the design of biosensors and their applications in improving the bioproduction of microbial cell factories through directed evolution.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1364-1373
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• 2004

Recently Evolvable Hardware (EHW) is widely studied to design effective hardware circuits that can reconfigure themselves according to the environment. However, it is still difficult to apply for complicated circuits because the search space increases exponentially as the complexity of hardware increases. To remedy this problem, this paper proposes a method to evolve complex hardware with a modular approach. The comparative experiments of some digital circuits with the conventional evolutionary approach indicate that the proposed method yields from 50 times to 1,000 times faster evolution and more optimized hardware.