• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.61-73
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• 2021

Metaheuristic search methods have been developed to solve problems with a range of purpose functions in situations lacking information and time constraints. In this study, the Hybrid Vision Correction Algorithm (HVCA), which enhances the performance of the Vision Correction Algorithm (VCA), was developed. The HVCA has applied two methods to improve the performance of VCA. The first method changes the parameters required by the user for self-adaptive parameters. The second method, the CGS structure of the Exponential Bandwidth Harmony Search With a Centralized Global Search (EBHS-CGS), was added to the HVCA. The HVCA consists of two structures: CGS and VCA. To use the two structures, a method was applied to increase the probability of selecting the structure with the optimal value as it was performed. The optimization problem was applied to determine the performance of the HVCA, and the results were compared with Harmony Search (HS), Improved Harmony Search (IHS), and VCA. The HVCA improved the number of times to find the optimal value during 100 repetitions compared to HS, IHS, and VCA. Moreover, the HVCA reduced the Number of Function Evaluations (NFEs). Therefore, the performance of the HVCA has been improved.

• Journal of Ship and Ocean Technology
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• v.11 no.2
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• pp.10-25
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• 2007

With the sharp increase of the oil price, the issue of the energy saving requires even higher propulsive efficiency of the propellers. Traditionally the propellers have been designed with the criteria such as that of Lerbs optimum based on the lifting line theory and the empirical formulae of Lerbs and van Manen giving relations of the wake pitch with the wake non-uniformity. With the aid of the high speed computer, it is now possible to apply the time-consuming iterative approaches for the solution of the lifting surface problems. In this paper we formulate the variational problem to optimize the efficiency of the propeller operating in the given ship wake using the lifting surface method. The variational formulation relating the spanwise circulation distribution with the propulsive efficiency to be maximized is however non-linear in circulation distribution functions, thus the iterative method is applied to the quasi-linearized equations. The blade shape design also requires the iterative procedures, because the shape of the blade which is represented by the lifting surface is unknown a priori. The numerical code was validated with the DTNSRDC propeller 4119 which is well-known to be optimum in uniform inflow condition. In addition existing (well-designed) commercial propellers were selected and compared with the results of the open water tests and the self-propulsion tests.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.79-89
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• 2016

In this paper, we proposed the object classification method using genetic and dynamic random forest consisting of optimal combination of unit tree. The random forest can ensure good generalization performance in combination of large amount of trees by assigning the randomization to the training samples and feature selection, etc. allocated to the decision tree as an ensemble classification model which combines with the unit decision tree based on the bagging. However, the random forest is composed of unit trees randomly, so it can show the excellent classification performance only when the sufficient amounts of trees are combined. There is no quantitative measurement method for the number of trees, and there is no choice but to repeat random tree structure continuously. The proposed algorithm is composed of random forest with a combination of optimal tree while maintaining the generalization performance of random forest. To achieve this, the problem of improving the classification performance was assigned to the optimization problem which found the optimal tree combination. For this end, the genetic algorithm methodology was applied. As a result of experiment, we had found out that the proposed algorithm could improve about 3~5% of classification performance in specific cases like common database and self infrared database compare with the existing random forest. In addition, we had shown that the optimal tree combination was decided at 55~60% level from the maximum trees.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.3-8
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• 2016

We propose a modified form of the decision-directed least mean square (DD LMS) algorithm that is widely used in the optimization of self-adaptive equalizers, and show the modified version greatly improves the initial convergence properties of the conventional algorithm. Existing DD LMS regards the difference between a equalizer output and a quantization value for it as an error, and achieves an optimization of the equalizer based on minimizing the mean squared error cost function for the equalizer coefficients. This error generating method is useful for binary signal or a single-level signals, however, in the case of multi-level signals, it is not effective in the initialization of the equalizer. The modified DD LMS solves this problem by modifying the error generation. We verified the usefulness and performance of the modified DD LMS through experiments with multi-level signals under distortions due to intersymbol interference and additive noise.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.5
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• pp.479-487
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• 2009

This paper describes the design of a full-spade twisted rudder section by using the genetic algorithm based on VLM(Vortex Lattice Method) and panel method. The developed propeller- rudder analysis program has been validated by comparing with experimental data. The developed code has been used for the design of a twisted full-spade rudder especially for finding out optimum section. The optimization has been firstly carried out by the genetic algorithm. The more detail variation of a rudder section has been also conducted by changing section profile in more detail to confirm the most optimum section profile. The developed new twisted rudder has been compared with existing twisted rudder by cavitation testing in the cavitation tunnel at MOERI. It is concluded that the developed twisted rudder has a lower cavity in comparison with existing twisted rudder. The verification of efficiency gain is expected to be carried out through self-propulsion tests in the near future.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.138-144
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• 2013

The automation technology for overlay welding is needed due to the occurrence of severe corrosion and abrasion on the surface of internal contact in different shape of fittings. In Korea, different shapes of fittings have been manufactured by using the imported equipment of overlay welding automation at some companies. Thus the research on the development of overlay welding automation system (in short, OWAS) for a large L-type tube is urgently needed. In this paper, the investigation is focused on the optimal design of a supporting base for the (currently developing) OWAS of large L-type tube. Specifically we assume that the base which supports the equipment during the process of overlay welding is loaded as self-weight in the direction of gravity through static analysis especially when it is rotated 180 degree on the OWAS. For optimal design of a supporting base for OWAS of large L-type tube, Solidworks(R) (for 3-dimensional modelling) and ANASYS Workbench(R) (for structural analysis) are incorporated so as to proceed an optimization routines based on Response Surface Method (RSM) and Design of Experiment (DOE). In more specific, DOE finds out major factors (or dimensions) of the supporting base by using MINITAB(R). Then the regression equations between design variables (the major factors of supporting base) and response variables (deformation, stress and safety factor for the supporting base), which will be resulted in by RSM, verify the major factors of DOE. In the next step, Central Composite Design (CCD) plans 20 simulations of ANASYS Workbench(R) and then figures out the optimal values of design variables which will be reflected on the manufacturing of supporting base. Finally welding experiment is conducted to figure out the influence of overlay welding quality in applying the optimized design values of supporting base to the actual OWAS.

• Korean Journal of Digital Imaging in Medicine
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• v.14 no.1
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• pp.1-6
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• 2012

This round of tests in patients with UGI and Esophagography data collected by national and international reference levels based on the original set of guidelines and fluoroscopy, through the provision of medical radiation exposure reduction and further optimization of Defense to realize that is intended. 359 names in our hospital underwent Esophagography 302 patients who underwent UGI average fluoroscopy time and number of images to calculate the average 21 cm Acryl phantom dose for 10 seconds and 20 seconds, average area dose and the area dose of 1 spot image, 5 spot consecutive images by measuring the patient dose and third quartile of the mean area dose was set seonryangin reference dose. Esophagography average patient dose was set to 30.05 $Gy{\cdot}cm^2$, DRL was set at a 25.37 $Gy{\cdot}cm^2$. Average dose of UGI patients were selected as 45.33 $Gy{\cdot}cm^2$, DRL was set at a 34 $Gy{\cdot}cm^2$. UGI patients with established average dose recommended in the 2008 national recommendation from the UGI examination with a dose of less than 49.7 $Gy{\cdot}cm^2$ seonryangin is evaluated. This Note examines the dose of self-aware through education recognizes the importance of dose reduction and examine if their efforts and further reduce patient dose could achieve optimization of the medical exposure is considered.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.757-764
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• 2017

As the reduction of greenhouse gases(GHGs) emission has become a global issue, the microgrid markets are growing rapidly. With the sudden changes in the market, Korean government suggested a new business model called 'Self-Sufficient Energy Islands'. Its main concern is a stand-alone microgrid composed of Distributed Energy Resources(DERs) such as Renewable Energy Sources(RESs), Energy Storage System(ESS) and Fuel Cell, in order to minimize the emission of GHGs. According to these trend, this paper is written to propose an optimal sizing method of DERs in a stand-alone microgrid by using Genetic Algorithm(GA), one of the representative stochastic methods. It is to minimize the net present cost with the variables, size of RESs and ESS. In the process for optimization, the sunless days are considered as additional constraints. Through the case study analysis, the size of DERs installed in a microgrid system has been computed using the proposed method in MATLAB. And the result of MATLAB is compared with that of HOMER(Hybrid Optimization of Multiple Energy Resources), a well-known energy modeling software.

• Smart Structures and Systems
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• v.22 no.1
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• pp.81-94
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• 2018

Automatic Generation Control (AGC) has functionally controlled the interchange power flow in order to suppress the dynamic oscillations of frequency and tie-line power deviations as a perturbation occurs in the interconnected multi-area power system. Furthermore, Flexible AC Transmission Systems (FACTS) can effectively assist AGC to more enhance the dynamic stability of power system. So, Static Synchronous Series Compensator (SSSC), one of the well-known FACTS devices, is here applied to accurately control and regulate the load frequency of multi-area multi-source interconnected power system. The research and efforts made in this regard have caused to introduce the Fractional Order Proportional Integral Derivative (FOPID) based SSSC, to alleviate both the most significant issues in multi-area interconnected power systems i.e., frequency and tie-line power deviations. Due to multi-objective nature of aforementioned problem, suppression of the frequency and tie-line power deviations is formularized in the form of a multi-object problem. Considering the high performance of Multi Objective Bees Algorithm (MOBA) in solution of the non-linear objectives, it has been utilized to appropriately unravel the optimization problem. To verify and validate the dynamic performance of self-defined FOPID-SSSC, it has been thoroughly evaluated in three different multi-area interconnected power systems. Meanwhile, the dynamic performance of FOPID-SSSC has been accurately compared with a conventional controller based SSSC while the power systems are affected by different Step Load Perturbations (SLPs). Eventually, the simulation results of all three power systems have transparently demonstrated the dynamic performance of FOPID-SSSC to significantly suppress the frequency and tie-line power deviations as compared to conventional controller based SSSC.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.694-705
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• 2010

The mutation operation is the main operation in the evolutionary programming which has been widely used for the optimization of real valued function. In general, the mutation operation utilizes both a probability distribution and its parameter to change values of variables, and the parameter itself is subject to its own mutation operation which requires other parameters. However, since the optimal values of the parameters entirely depend on a given problem, it is rather hard to find an optimal combination of values of parameters when there are many parameters in a problem. To solve this shortcoming at least partly, if not entirely, in this paper, we propose a new mutation operation in which the parameter for the variable mutation is theoretically estimated from the self-adaptive perspective. Since the proposed algorithm estimates the scale parameter of the Cauchy probability distribution for the mutation operation, it has an advantage in that it does not require another mutation operation for the scale parameter. The proposed algorithm was tested against the benchmarking problems. It turned out that, although the relative superiority of the proposed algorithm from the optimal value perspective depended on benchmarking problems, the proposed algorithm outperformed for all benchmarking problems from the perspective of the computational time.