• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2038-2057
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• 2017

Gaussian learning is a new technology in the computational intelligence area. However, this technology weakens the learning ability of a particle swarm and achieves a lack of diversity. Thus, this paper proposes a vector Gaussian learning strategy and presents an effective approach, named particle swarm optimization based on vector Gaussian learning. The experiments show that the algorithm is more close to the optimal solution and the better search efficiency after we use vector Gaussian learning strategy. The strategy adopts vector Gaussian learning to generate the Gaussian solution of a swarm's optimal location, increases the learning ability of the swarm's optimal location, and maintains the diversity of the swarm. The method divides the states into normal and premature states by analyzing the state threshold of the swarm. If the swarm is in the premature category, the algorithm adopts an inertia weight strategy that decreases linearly in addition to vector Gaussian learning; otherwise, it uses a fixed inertia weight strategy. Experiments are conducted on eight well-known benchmark functions to verify the performance of the new approach. The results demonstrate promising performance of the new method in terms of convergence velocity and precision, with an improved ability to escape from a local optimum.

• Bulletin of the Korean Chemical Society
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• 제25권7호
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• pp.997-1002
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• 2004

A hydrogenperoxide sensor containing peroxidase extracted from horseradish was constructed and pH effect on its sensing ability was investigated. Current profiles of the biosensor with pH and the electrophoretic analysis showed that horseradish peroxidase consists of two isozymes. Assuming that it is a hypothetical twoisozyme mixture, the current profiles were deconvoluted into two Gaussians. Application of the new Michaelis-Menten equation connoting pH concept to this system enabled to find all the related dissociation constants of the isozyme-substrates and the isozyme-proton complexes and to determine pHs for the maximal isozyme activities.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.490-495
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• 1992

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming cooperates with neural identification network is used to generate the optimum control law for the complicate continuous/batch chemical reactor systems that have inherent nonlinear dynamics. Based on our approach, we developed a neural model predictive controller(NMPC) which shows excellent performances on nonlinear, model-plant mismatch cases of chemical reactor systems.

• Journal of Microbiology
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• 제41권2호
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• pp.169-173
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• 2003

A treatability investigation was conducted to determine if landfarming would be effective for the remediation of unsanitary landfill waste soils. Calculations based on biodegradable organic carbon contents and initial CO$_2$ evolution rates revealed that landfarming has a high potential for landfill site remediation and that the optimum strategy for bioremediation is site-specific.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 C
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• pp.1207-1209
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• 1994

An optimization technique applicable to the Yagi-Uda antenna was proposed in this paper. An objective function, which is the gain of the antenna in our case, was computed using method of moments. Design variables for the Yagi-Uda antenna were chosen with lengths, positions and diameters of the antenna elements. For the optimization process, the evolution strategy technique was adopted. The results were compared with existing results and showed better performances.

• 산업경영시스템학회지
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• 제16권28호
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• pp.129-135
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• 1993

Quality is become not only the most critical component of manufacturing strategy but also the most critical measure of performance and justification of advanced manufacturing system. The objective of this paper is to offer classification & optimum concept of quality-cost and to illustrate a method of evaluation quality-cost then a case example is presented to illustrate the result of quantifying the suggested formula and these values are given to justify of management.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.899-902
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• 1993

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

• 한국건설순환자원학회논문집
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• 제5권3호
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• pp.230-238
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• 2017

탄산화는 지하구조물에서 발생하는 대표적인 열화현상으로 내구성 문제를 야기하며, 이는 보수를 통하여 사용성능을 확보해야 한다. 본 연구는 확률론적인 방법을 고려하여 최적의 보수시기를 도출하며 초기 및 보수조건을 고려하여 복잡한 확률 해석 없이 최적의 보수시기 도출식을 제안하는 것이다. 이를 위해 초기시공에 따른 내구수명, 보수를 통해 연장된 내구수명, 그리고 각각의 변동성을 고려하여 보수횟수를 감소시킬 수 있는 기간을 평가하였다. 각각의 기간을 독립적으로 가정하여 10~50년간의 해석을 수행하였으며, 최적의 보수시기를 평가할 수 있는 식을 회귀분석을 통해 제안하였다. 변동계수의 변화는 보수횟수를 줄이는 데 큰 영향을 주지 못하지만 임계시점에서의 확률변화에 큰 영향을 주었다. 또한 보수재를 통한 내구수명의 증가는 보수횟수를 줄이는 데 큰 역할을 하였다. 제안된 식은 정량적인 수명의 변동성을 정의한다면 효과적인 유지관리 기법으로 사용될 수 있다.

• 한국자동차공학회논문집
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• 제22권3호
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• pp.81-89
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• 2014

This study researched on the effect of HP/LP-EGR system to improve fuel consumption of Low Temperature Combustion Engine. Firstly, low temperature combustion engine with HP/LP-EGR system was established using 6.0L wastegate turbocharger HDDI engine. And suppliable EGR rate of the engine was proven to be enough to realize stable low temperature combustion. Then, optimum operating strategy was founded to develop fuel consumption of the engine. Control parameters were HP/LP-EGR valve and IPCV(Intake Pressure Control Valve) duty. Experiments method was that characteristics of the engine were measured and analyzed according to HP/LP-EGR strategies while EGR rate was fixed. Operating range for the strategy were divided into three parts, low load for low temperature combustion, high load for conventional diesel combustion, and transient condition. Finally, with the above strategy of this study, BSFC of the engine was improved about 2% compared to the base engine, and emission level, NOx and PM, met Tier4Final emission regulation.

• 대한교통학회지
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• 제24권7호
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• pp.65-79
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• 2006

ITS 의 한 분야인 첨단교통정보체계 (ATIS: Advance Traveler Information System)는 운전자들에게 통행 전 (pre-trip). 통행 중 (en-route) 교통정보를 제공함으로서 운전자의 경로선택과정에 영향을 미쳐 도로망의 교통량 분산효과를 추구하는 시스템이다. 이중 도로상에서 운전자가 진행하는 방향에 대한 직접적인 정보를 제공하는 VMS 는 ATIS의 정보제공방안중 가장 효과적인 수단이 될 수 있다. 이러한 때 VMS의 정보제공목표는 단순현황정보만을 제공하는 운전자 편의측면과 교통수요를 관리하여 시스템의 성능을 증진시키는 시스템 제어측면으로 구분이 가능하다 하지만 보다 효율적인 도로전광표지의 정보제공을 위해서는 시스템제어 측면의 정보제공이 이루어져야 할 것이다 이러한 교통관리시스템(traffic management system)으로서 VMS 핵심적인 관리전략은 혼잡 (traffic congestion) 또는 돌발 상황(incident)발생 시 지체 (delay)를 최소하기 위한 교통우회전략(Traffic Diversion Strategy)이라 할 수 있다 이를 효과적으로 운영하기 위해서는 첫째, 교통상황 (network traffic condition)에 따라 적정한 우회교통량 (diversion traffic volume) 의 산정이 선행되어야 하고 둘째, 이러한 우회교통량을 제어하기 위해서는 VMS 정보내용 (VMS massage contents)에 따른 운전자의 행태(driver response behavior)가 반영된 정보제공전략 (providing information strategy)이 수립되어야 한다. 이에 본 연구에서는 돌발 상황 발생에 의해 혼잡이 야기될 때 VMS 실시간 경로안내 정보제공에 대해 초점을 맞추었다 이를 위해 첫째로, CA(Cellular Automata) 기반 교통류 사율레이션을 모형을 이용뼈 통행시간 및 대기행렬의 변화가 반영된 시간대별 시스템 최적경로 전환율을 산정하였다. 둘째로, 이항로짓 모형을 이용하여 운영자가 제어할 수 있는 정보특성에 대한 경로전환행태 모형 (route choice behavior model) 을 만들었다 마지막으로 시스템 최적상태 (system Optimum)의 달성을 위한 VMS의 시간대별 정보내용 및 강도를 결정하였다.