• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1210-1218
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• 2011

GA (Genetic Algorithms) are efficient for searching for global optima but may have some problems such as premature convergence, convergence to local extremum and divergence. These phenomena are related to the evolutionary operators. As population diversity converges to low value, the search ability of a GA decreases and premature convergence or converging to local extremum may occur but population diversity converges to high value, then genetic algorithm may diverge. To guarantee that genetic algorithms converge to the global optima, the genetic operators should be chosen properly. In this paper, we analyze the effects of the selection operator, crossover operator, and mutation operator on convergence properties, and propose the sweeping method of mutation probability and elitist propagation rate to maintain the diversity of the GA's population for getting out of the premature convergence. Results of simulation studies verify the feasibility of using these sweeping operators to avoid premature convergence and convergence to local extrema.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.170-177
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• 2014

Genetic Algorithms are robust search and optimization techniques but have some problems such as premature convergence and convergence to local extremum. As population diversity converges to low value, the search ability decreases and converges to local extremum but population diversity converges to high value, then the search ability increases and converges to global optimum or genetic algorithm may diverge. To guarantee that genetic algorithms converge to the global optima, the genetic operators should be chosen properly. In this paper, we propose the genetic operators with the hybrid function of the average Hamming distance and the fitness value to maintain the diversity of the GA's population for escaping from the premature convergence. Results of simulation studies verified the effects of the mutation operator for maintaining diversity and the other operators for improving convergence properties as well as the feasibility of using proposed genetic operators on convergence properties to avoid premature convergence and convergence to local extremum.

• Bulletin of the Society of Naval Architects of Korea
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• v.23 no.2
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• pp.27-32
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• 1986

This paper describes an application of the adaptive finite element computations to a free surface flow problem in a canal. A-posteriori error estimates for the adaptive finite element computations are based on the dual extremum principles. Previously the dual extremum principles were applied to compute the upper and lower bounds of the added mass of two-dimensional cylinders in a canal[1,2]. However, the present method improves the convergence of the computed results by utilizing the local error estimates and by applying the adaptive meshes in the finite element computations. In a test result using triangular elements it is shown that the numerical error in the adaptive finite elements reduces quadratically compared with that in a uniform mesh subdivision.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.1
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• pp.197-206
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• 1990

Numerical results of heat transfer from a horizontal isothermal surface are presented for wall temperature T$_{w}$ = 0 .deg. C and ambient water temperature, T$_{\infty}$, from 1 .deg. C to 15 .deg. C. They include streamlines, temperature profiles, local heat transfer coefficients and average Nusselt numbers for the entire flow fields. For a upward-facing horizontal isothermal surface, the results show steady two dimensional flow regimes for T$_{\infty}$ .leg. 4.4 .deg. C, but no solution was obtained above T$_{\infty}$ = 4.4 .deg. C. For a downward-facing horizontal isothermal surface, the flow regimes are steady two dimensional flow for T$_{\infty}$ .geq. 4.9 .deg. C, and the numerical calculation was failed below this ambient water temperature. The mean Nusselt number has its maximum value at about T$_{\infty}$ = 3.4 .deg. C for upward-facing horizontal isothermal surface. For the case of downward-facing horizontal isothermal surface, the mean Nusselt number increases as the ambient water temperature increases.es.s.s.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.6
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• pp.1195-1204
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• 1992

The natural convection from upward and downward facing horizontal isothermal plate immersed in water is studied numerically. The temperature of the plate is from 0.0 .deg. C to 8.0 .deg. C and the ambient water temperature is from 1.0 .deg. C to 10.0 .deg. C. Numerical results are presented for the velocity profiles, temperature profiles, local heat transfer coefficients, and average Nusselt numbers over the entire flow fields. Flow patterns are shown in the upward and downward facing surfaces at different ambient water temperatures. For the upward facing surface, there are upflow and unsteady flow. And the regions of the ambient water temperatures which give rise to the upflow are more extensive as the temperatures of the isothermal surface become more distant from the density extremum temperature. For the downward facing surface, only the downflow region is shown. For the upward facing horizontal isothermal surface, the average Nusselt number(= N $u_{1}$$^{*}$) is 28.86(Ra)$^{0.01}$. And for the downward facing surface, the average Nusselt number(= N $u_{2}$$^{*}$) is $C_{2}$(Ra)$^{0.2}$ and the values of $C_{2}$ are enlarged in the range of 0.785 .leq. $C_{2}$ .leq. 1.250 as increasing of the temperatures of the isothermal surface.ace.ace.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.5
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• pp.510-516
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• 2015

This paper describes an approach to detect interesting objects using satellite images. This paper focuses on the interesting objects that have common special patterns but do not have identical shapes and sizes. The previous technologies are still insufficient for automatic finding of the interesting objects based on operation of special pattern analysis. In order to overcome the circumstances, this paper proposes a methodology to obtain the special patterns of interesting objects considering their common features and their related characteristics. This paper applies MSER(Maximally Stable Extremal Regions) for the region detection and corner detector in order to extract the features of the interesting object. This paper conducts a case study and obtains the experimental results of the case study, which is efficient in reducing processing time and efforts comparing to the previous manual searching.

• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.432-442
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• 2019

Most current human action recognition methods based on deep learning methods. It is required, however, a very high computational cost. In this paper, we propose an action change detection method to reduce repetitive human action recognition tasks. In reality, simple actions are often repeated and it is time consuming process to apply high cost action recognition methods on repeated actions. The proposed method decides whether action has changed. The action recognition is executed only when it has detected action change. The action change detection process is as follows. First, extract the number of non-zero pixel from motion history image and generate one-dimensional time-series data. Second, detecting action change by comparison of difference between current time trend and local extremum of time-series data and threshold. Experiments on the proposed method achieved 89% balanced accuracy on action change data and 61% reduced action recognition repetition.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.624-630
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• 2010

As electrocardiogram(ECG) signals are generally sampled with a frequency of over 200Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently. In this paper, an ECG signal compression method, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes are extracted with the proposed method, which uses local extremum of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes are added according to the iterative vertex selection method. Through the experimental results on the ECG signals from MIT-BIH Arrhythmia database, it is concluded that the vertexes selected by the proposed method preserve all feature points of the ECG signals. In addition, they are more efficient than the AZTEC(Amplitude Zone Time Epoch Coding) method.