• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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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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• v.25 no.7
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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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• 1992.10a
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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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• v.41 no.2
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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.

• Proceedings of the KIEE Conference
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• 1994.07b
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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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.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.3
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• pp.230-238
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• 2017

Carbonation is a representative deterioration for underground structure, which causes additional repair for service life. This study proposes a simplified equation for optimum repair timing without complicated probability calculation, considering initial and repair conditions For the work, initial service life, extended service life through repair, and their COVs(Coefficient of Variation) are considered, and the periods which can reduce number of repair are evaluated. Assuming the two service lives to be independent, the repair timings are derived from 10 to 50 years based on the probabilistic method, and the regression analysis technique for optimum repairing timing is proposed. Decreasing COV has insignificant effect on reducing repairing number but shows a governing effect on changes in probability near the critical repairing stage. The extension of service life through repairing is evaluated to be a critical parameter for reducing repairing number. The proposed technique can be efficiently used for maintenance strategy with actual COV of initial and additional service life due to repairing.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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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.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.65-79
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• 2006

The ATIS(Advance Traveler Information System), as one part of ITS, is a system aiming to disperse traffic volume on transportation networks by providing traffic information to transportation users on pre-trip and en-route trips. One of tools in ATIS is usage of VMS(Variable Message Signs). It provides to the drivers with direct information about state of processing direction. which is considered as the most effective method in ATIS. The purposes of providing VMS information are classified two categories. One is to provide simple information to drivers for their convenience. The other is to manage traffic demand to improve transportation network performance. However, for more effective and reliable VMS information, several strategies should be taken into account. The main VMS management strategy is "Traffic Diversion Strategy for minimum delay" when traffic congestion or incident are occurred. For effective operation. firstly. reasonable diversion traffic volume is determined by network traffic condition Secondly, it is necessary to make providing information strategy which reflects driver response behavior for controling diversion traffic volume. This paper focuses on the providing real-time route guidance information by VMS when congestion is occurred by the incidents. This sturdy estimates time-dependent system optimal diversion rate that inflects travel time and queue lengths using traffic flow simulation model on base Cellular Automata. In addition, route choice behavior models are developed using binary logit model for traffic information variable by traffic system controller. Finally, this study provides time-dependent VMS massage contents and degree of providing information in order to optimize the traffic flow.