• Journal of Korean Society of Water and Wastewater
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• 제32권2호
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• pp.115-122
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• 2018

Direct spring loaded pressure relief valve(DSLPRV) is a safety valve to relax surge pressure of the pipeline system. DSLPRV is one of widely used safety valves for its simplicity and efficiency. However, instability of the DSLPRV can caused by various reasons such as insufficient valve volume, natural vibration of the spring, etc. In order to improve reliability of DSLPRV, proper selection of design factors of DSLPRV is important. In this study, methodology for selecting design factors for DSLPRV was proposed. Dynamics of the DSLPRV disk was integrated into conventional 1D surge pressure analysis. Multi-objective genetic algorithm was also used to search optimum design factors for DSLPRV.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.113-116
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• 1994

In this paper. we suggest new fuzzy modeling algorithm, which can be easily implemented, by combining HPC-MEANS Algorithm and Genetic Algorithm. HPC-MEANS used to cluster the sample data in input-output space will hyper planes and to make structure identification roughly and Genetic Algorithm is used to nine the premise and consequent parameters. For the validity of suggested methods we model the system with I/O data from known system. and then compare two systems.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.942-944
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• 1999

This paper presents a genetic learning algorithm with partial update technique in application to active control system. Proposed algorithm divides active control system into two parts, real time control part and control parameter update part. This genetic algorithm has global convergent advantage and is expected to be applied easily to real time active noise and vibration control systems. Computer simulation was performed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.185-191
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• 2006

As development of information technology, companies stress the need of knowledge management. Companies construct ERP system including knowledge management. But, it is not easy to formalize knowledge in organization. They experience that constructing information system help knowledge management. Now, we focus on engineering knowledge. Because engineering data contains experts' experience and know-how in its own, engineering knowledge is a treasure house of knowledge. Korean shipyards are leader of world shipbuilding industry. They have accumulated a store of knowledges and data. But, they don't have data minning tool to utilize accumulated data. This paper treats development of data minning tools for the utilization of shipbuilding knowledge based on genetic programming (GP).

• Journal of Electrical Engineering and Technology
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• 제5권4호
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• pp.597-605
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• 2010

This paper presents a contribution to parameter identification of a non-linear system using a new strategy to improve the genetic algorithm (GA) method. Since cost function plays an important role in GA-based parameter identification, we propose to improve the simple version of GA, where weights of the cost function are not taken as constant values, but varying along the procedure of parameter identification. This modified version of GA is applied to the induction motor (IM) as an example of nonlinear system. The GA cost function is the weighted sum of stator current and rotor speed errors between the plant and the model of induction motor. Simulation results show that the identification method based on improved GA is feasible and gives high precision.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제32권11호
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• pp.924-929
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• 2008

The rate of wear of cam followers in a valve train system is mainly a function of contact stress between the cam and the follower, sliding velocity and hydrodynamic film thickness between the two mating surfaces. The wear or surface fatigue can be reduced by maximizing the elastohydrodynamic film thickness. In this paper, an attempt has been made to estimate the optimal specific film thickness of cam-follower system quantitatively. A general TES polynomial function with real values of exponents is developed and genetic algorithm (GA) is used as optimization techniques for maximizing the minimum specific film thickness. The optimization programs enumerate values of the exponents for synthesis of cam displacement curves. The results show that the minimum film thickness can be increased considerably, e.g. approximately 7% in this paper.

• Journal of the Institute of Convergence Signal Processing
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• 제11권3호
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• pp.250-254
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• 2010

As the number of input and fuzzy set of a fuzzy system increase, the size of the rule base increases exponentially and becomes unmanageable (curse of dimensionality). In this paper, tree architectures of fuzzy controller (TAFC) is proposed to overcome the curse of dimensionality problem occurring in the design of fuzzy controller. TAFC is constructed with the aid of AND and OR fuzzy neurons. TAFC can guarantee reduced size of rule base with reasonable performance. For the development of TAFC, genetic algorithm constructs the binary tree structure by optimally selecting the nodes and leaves, and then random signal-based learning further refines the binary connections (two-step optimization). An inverted pendulum system is considered to verify the effectiveness of the proposed method by simulation.

• Journal of Crop Science and Biotechnology
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• 제11권4호
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• pp.233-236
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• 2008

A positive selectable marker system was adapted for transformation of mature embryo-derived calli of Indica rice (Oryza sativa L.) utilizing the PMI gene encoding for phosphomannose-isomerase that converts mannose-6-phosphate to fructose-6-phosphate. The transformed cells grew on medium supplemented with 3% mannose as carbon source and calli were selected on media containing various concentrations of mannose. Molecular analyses showed that the transformed plants contained the PMI gene. The results indicate that the mannose selection system can be used for Agrobacterium-mediated transformation of mature embryo in rice to substitute the use of conventional selectable markers in genetic transformation.

• Proceedings of the KIEE Conference
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2486-2489
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• 2002

Pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제26권4호
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• pp.31-41
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• 2003

This paper deals with a cell formation problem for a set of m-machines and n-processing parts. Generally, a cell formation problem is known as NP-completeness. Hence the cell formation problem with multiple objectives is more difficult than single objective problem. The paper considers multiple objectives; minimize number of intercell movements, minimize intracell workload variation and minimize intercell workload variation. We propose a multiple objective genetic algorithms(MOGA) resolving the mentioned three objectives. The MOGA procedure adopted Pareto optimal solution for selection method for next generation and the concept of Euclidean distance from the ideal and negative ideal solution for fitness test of a individual. As we consider several weights, decision maker will be reflected his consideration by adjusting high weights for important objective. A numerical example is given for a comparative analysis with the results of other research.