• 한국유체기계학회 논문집
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• 제14권1호
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• pp.34-41
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• 2011

Fire characteristics can be analyzed more realistically by using more accurate properties related to the fire dynamics and one way to acquire these fire properties is to use one of the inverse property estimation techniques. In this study two optimization algorithms which are frequently applied for the inverse heat transfer problems are selected to demonstrate the procedure of obtaining pyrolysis properties of charring material with relatively simple thermal decomposition. Thermal decomposition is occurred at the surface of the charring material heated by receiving the radiative energy from external heat sources and in this process the heat transfer through the charring material is simplified by an unsteady 1-dimensional problem. The basic genetic algorithm(GA) and repulsive particle swarm optimization(RPSO) algorithm are used to find the eight properties of a charring material; thermal conductivity(virgin, char), specific heat(virgin, char), char density, heat of pyrolysis, pre-exponential factor and activation energy by using the surface temperature and mass loss rate history data which are obtained from the calculated experiments. Results show that the RPSO algorithm has better performance in estimating the eight pyrolysis properties than the basic GA for problems considered in this study.

• Structural Engineering and Mechanics
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• 제68권5호
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• pp.549-561
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• 2018

Sobol method is applied as a powerful variance decomposition technique in the field of global sensitivity analysis (GSA). The paper is devoted to increase convergence speed of the extracted Sobol indices using a new proposed sampling technique called genetic based Latine hypercube sampling (GBLHS). This technique is indeed an improved version of restricted Latine hypercube sampling (LHS) and the optimization algorithm is inspired from genetic algorithm in a new approach. The new approach is based on the optimization of minimax value of LHS arrays using manipulation of array indices as chromosomes in genetic algorithm. The improved Sobol method is implemented to perform factor prioritization and fixing of an uncertain comprehensive high speed rotor-bearing system. The finite element method is employed for rotor-bearing modeling by considering Eshleman-Eubanks assumption and interaction of axial force on the rotor whirling behavior. The performance of the GBLHS technique are compared with the Monte Carlo Simulation (MCS), LHS and Optimized LHS (Minimax. criteria). Comparison of the GBLHS with other techniques demonstrates its capability for increasing convergence speed of the sensitivity indices and improving computational time of the GSA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2702-2719
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• 2013

A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

• 센서학회지
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• 제20권3호
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.89-92
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• 2000

In this paper, an effective image restoration using Genetic Algorithm(GA) in wavelet transform region is proposed. First, a wavelet transform is used for decomposition of a blurred image with white Gaussian noise as a preprocessing of the proposed method. The wavelet transform decomposes a degraded image into a wavelet subband coefficient planes. In this wavelet transformed subband coefficient planes, three highest subbands is composed entirely of noise elements on a degraded image. So, these subbands are removed. And remained subbands except for the lowest subband are individually applied to GA. For the performance evaluation, the proposed method is compared with a conventional single GA algorithm and a conventional hybrid method of wavelet transform and GA for a Lenna image and a boat image. As an experimental result, the proposed algorithm is prior to a conventional methods as each PSNR 3.4dB, 1.3dB.

• 산업공학
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• 제13권3호
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• pp.479-485
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• 2000

We consider a Location-Allocation Problem with the Cost of Land(LAPCL). LAPCL has extremely huge size of problem and complex characteristic of location and allocation problem. Heuristics and decomposition approaches on simple Location-Allocation Problem were well developed in last three decades. Recently, genetic algorithm(GA) is used widely at combinatorics and NLP fields. A lot of research shows that GA has efficiency for finding good solution. Our main motive of this research is developing of a package for LAPCL. We found that LAPCL could be reduced to trivial problem, if locations were given. In this case, we can calculate fitness function by simple technique. We built a database constructed by zipcode, latitude, longitude, administrative address and posted land price. This database enables any real field problem to be coded into a mathematical location problem. We developed a package for a class of multi-location problem at PC. The package allows for an interactive interface between user and computer so that user can generate various solutions easily.

• 한국국방경영분석학회지
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• 제25권2호
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• pp.117-129
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• 1999

We consider a Location-Allocation Problem with the Cost of Land(LAPCL). LAPCL has extremely huge size of problem and complex characteristic of location and allocation problem. Heuristics and decomposition approaches on simple Location-Allocation Problem were well developed in last three decades. Currently, genetic algorithm(GA) is used widely at combinatorics and NLP fields. A lot of research show that GA has efficiency for finding good solution. Our main motive of this research is developing of a GA in LAPCL. We found that LAPCL could be reduced to trivial problem, if locations were given. In this case, we can calculate fitness function by simple technique. We propose fourth alternative genetic algorithm. Computational experiments are carried out to find a best algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.3042-3044
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• 1999

This paper presents a method for solving the path planning problem for robot manipulators. The technique allows manipulators to move from a specified starting point to a goal without colliding with objects in two dimensional environment. Approximate cell decomposition with a greedy depth-first search algorithm is used to guide the end effector though Cartesian space and genetic algorithms are used to solve the joint variable for the robot manipulators.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.167-170
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• 2004

This paper proposes resource allocation method for achieving investment goals in manufacturing system. In order to align resource allocation and manufacturing system design, the system design decomposition (SDD) approach is used. In this paper, a mathematical formulation for resource allocation based on SDD approach is analyzed and a genetic algorithm application is discussed.

• Structural Engineering and Mechanics
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• 제14권6호
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• pp.625-647
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• 2002

Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.