• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.267-270
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• 1997

In this paper, we proposed an optimazation method using Genetic Algorithm for nonlinear system modeling. Fuzzy Neural Network(FNNs) was used as basic model of nonlinear system. FNNs was fused of Fuzzy Inference which has linguistic property and Neural Network which has learning ability and high tolerence level. This paper, We used FNNs which was proposed by Yamakawa. The FNNs was composed Simple Inference and Error Back Propagation Algorithm. To obtain optimal model, parameter of membership function, learning rate and momentum coefficient of FNNs are tuned using genetic algorithm. And we used simplex algorithm additionaly to overcome limit of genetic algorithm. For the purpose of evaluation of proposed method, we applied proposed method to traffic choice process and waste water treatment process, and then obtained more precise model than other previous optimization methods and objective model.

• 대한산업공학회지
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• 제36권3호
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• pp.164-175
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• 2010

In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.

• 대한전기학회논문지:전력기술부문A
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• 제49권3호
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• pp.85-94
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• 2000

In this paper, a robust H$\infty$ optimal tuning problem of a structure-specified PSS is investigated for power systems with parameter variation and disturbance uncertainties. Genetic algorithm is employed for optimization method of PSS parameters. The objective function of the optimization problem is the H$\infty$-norm of a closed loop system. The constraint of the optimization problem are based on the stability of the controller, limits on the values of the parameters and the desired damping of the dominant oscillation mode. It is shown that the proposed H$\infty$ PSS tuned using genetic algorithm is more robust than conventional PSS.

• Computers and Concrete
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• 제19권6호
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• pp.651-658
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• 2017

High-performance concrete, besides aggregate, cement, and water, incorporates supplementary cementitious materials, such as fly ash and blast furnace slag, and chemical admixture, such as superplasticizer. Hence, it is a highly complex material and modeling its behavior represents a difficult task. This paper presents an evolutionary system for the prediction of high performance concrete strength. The proposed framework blends a recently developed version of genetic programming with a local search method. The resulting system enables us to build a model that produces an accurate estimation of the considered parameter. Experimental results show the suitability of the proposed system for the prediction of concrete strength. The proposed method produces a lower error with respect to the state-of-the art technique. The paper provides two contributions: from the point of view of the high performance concrete strength prediction, a system able to outperform existing state-of-the-art techniques is defined; from the machine learning perspective, this case study shows that including a local searcher in the geometric semantic genetic programming system can speed up the convergence of the search process.

• Journal of Microbiology and Biotechnology
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• 제16권11호
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• pp.1678-1683
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• 2006

A novel suspension-phase enzyme reaction system for the intermolecular transglycosylation of L-ascorbic acid into 2-O-${\alpha}$-D-glucopyranosyl L-ascorbic acid supplementing extrusion starch as the glycosyl donor was developed using cyclodextrin glucanotransferase from Thermoanaerobacter sp. A high conversion yield compared to the conventional soluble-phase enzyme reaction system using cyclodextrins and soluble starch was achieved. The optimal reaction conditions were 2,000 units of cycIodextrin glucanotransferase, 20 g/l of L-ascorbic acid, and 50 g/l of extrusion starch at $50^{\circ}C$ for 24 h. The new suspension-phase enzyme reaction system also exhibited several distinct advantages other than a high conversion yield, including a lower accumulation of oligosaccharides and easily separable residual extrusion starch by centrifugation or filtration in the reaction mixture, which will facilitate the purification of 2-O-${\alpha}$-D-glucopyranosyl L-ascorbic acid. The new suspension-phase enzyme reaction system seems to be potentially applicable as the industrial process for the production of thermally and oxidatively stable 2-O-${\alpha}$-D-glucopyranosyl L-ascorbic acid.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.263-268
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• 2001

In this paper, we present a new heuristic algorithm fur buffer allocation in FMS (Flexible Manufacturing System). It is conducted by using a genetic algorithm and simulation. First, we model the system by using a simulation software, \"Arena\". Then, we apply a genetic algorithm to achieve an optimal solution. VBA blocks, which are kinds of add-in functions in Arena, are used to connect Arena with the genetic algorithm. The system being modeled has seven workstations, one loading/unloading station, and three AGVs (Automated Guided Vehicle). Also it contains three products, which each have their own machining order and processing times. We experimented with two kinds of buffer allocation problems with a proposed heuristic algorithm, and we will suggest a simple heuristic approach based on processing times and workloads to validate our proposed algorithm. The first experiment is to find a buffer profile to achieve the maximum throughput using a finite number of buffers. The second experiment is to find the minimum number of buffers to achieve the desired throughput. End of this paper, we compare the result of a proposed algorithm with the result of a simple buffer allocation heuristic based on processing times and workloads. We show that the proposed algorithm increase the throughput by 7.2%.t by 7.2%.

• 경영과학
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• 제24권2호
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• pp.143-155
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• 2007

The purpose of this paper is to develop a new method for information system sizing and selection based on a hybrid mixture of simulation and genetic algorithm, and to show its cost-effectiveness by applying it to a real world problem. To serve this purpose, we propose an operational model which identifies a set of system alternatives using simulation, and determines the optimal one using genetic algorithm. Specifically, with simulation, we generate probability distributions describing real data gathered from actual system, which can overcome the major weakness of the existing methodology that normally employs point estimates of the actual data and constant correction factors without theoretical rationale. We next search for the optimal combination of H/W, the number of CPUs, and S/W, which meets both of our business goals of incurring low TCO(total cost of ownership) and maintaining a good level of transaction processing performance. Experimental result shows the proposed method in this paper saves the cost while it preserves the system's capacity within allowable performance range.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.69.3-69
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• 2002

The reliability of system is to become a important concern in developed industry. The controller based on the reliability is so important position. A reliable system is for system protection and human life by fault detection and control action against the transient condition of system. The aerospace system , nuclear reactor and chemical reactor are representative of a reliable system. This paper presents analysis of reliable system reliability, formal problem statement of optimal redundancy based on the reliability for a reliable system. And the problem is optimized by genetic algorithm. The genetic algorithms is useful algorithm in case of...

• Journal of Microbiology and Biotechnology
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• 제25권11호
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• pp.1819-1826
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• 2015

Poly(ε-ʟ-lysine) (ε-PL) is a novel bioactive polymer secreted by filamentous bacteria. Owing to lack of a genetic system for most ε-PL-producing strains, very little research on enhancing ε-PL biosynthesis by genetic manipulation has been reported. In this study, an effective genetic system was established via intergeneric conjugal transfer for Streptomyces albulus PD-1, a famous ε-PL-producing strain. Using the established genetic system, the Vitreoscilla hemoglobin (VHb) gene was integrated into the chromosome of S. albulus PD-1 to alleviate oxygen limitation and to enhance the biosynthesis of ε-PL in submerged fermentation. Ultimately, the production of ε-PL increased from 22.7 g/l to 34.2 g/l after fed-batch culture in a 5 L bioreactor. Determination of the oxygen uptake rate, transcriptional level of ε-PL synthetase gene, and ATP level unveiled that the expression of VHb in S. albulus PD-1 enhanced ε-PL biosynthesis by improving respiration and ATP supply. To the best of our knowledge, this is the first report on enhancing ε-PL production by chromosomal integration of the VHb gene in an ε-PL-producing strain, and it will open a new avenue for ε-PL production.

• 한국항해항만학회지
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• 제28권3호
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• pp.221-225
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• 2004

본 논문은 신경 회로망과 유전 알고리즘을 이용한 비선형 시스템 모델링을 다룬다. 비선형 함수의 근사성 때문에 시스템을 식별하고 제어하기 위해서 신경 회로망을 응용한 연구가 실제로 많이 이루어지고 있다. 빠른 응답시간과 최소의 오차를 위해서는 최적구조 신경 회로망을 설계하는 것이 중요하다. 유선 알고리즘은 최근에 단순성과 견고성 때문에 점점 많이 이용되는 추세이다. 따라서 본 논문에서는 유선알고리즘을 이용하여 신경회로망을 최적화한다. 오차와 응답시간을 최소화하는 신경 회로망 구조를 위해서 유전알고리즘의 유전자로 이진 코딩하여 최적 신경회로망을 탐색하고자 한다. 시뮬레이션을 통해서, 최적 신경회로망 구조가 비선형 시스템 식별에 효과적인 것을 입증하고자 한다.