• Magazine of the Korean Society of Agricultural Engineers
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• v.42 no.4
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• pp.76-86
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• 2000

The objective function of reservoir storage error was suggested to simulate daily reservoir inflow. DAWAST model, UMAX, LMAX, FC,CP, CE were calibrated. Daily reservoir inflow was imulated with calibrated parameters and reservoir storage was simulated on a daily basis. The simulated results were compared with the monthly results by Gajiyama equation and ten-day results by Tank rainfall-runoff model through equal value lines and hydrographs . DAWAST model showed the best results compared with Gajiymama equation and Tank model. Especially, DAWAST model showed a good agreement in dry periods. NEW concept using objective function of storage error was believed to be satisfactory and to be applied in estimating reservoir inflow.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5328-5346
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• 2016

An optimal power control algorithm based on convex optimization is proposed for base stations in long term evolution networks. An objective function was formulated to maximize the proportional fairness of the networks. The optimal value of the objective function was obtained using convex optimization and distributed methods based on the path loss model between the base station and users. Field tests on live networks were conducted to evaluate the performance of the proposed algorithm. The experimental results verified that, in a multi-cell multi-user scenario, the proposed algorithm increases system throughputs, proportional fairness, and energy efficiency by 9, 1.31 and 20.2 %, respectively, compared to the conventional fixed power allocation method.

• Korean Journal of Optics and Photonics
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• v.25 no.1
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• pp.8-13
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• 2014

By using finite ray-tracing and curve fitting, a numerical method to determine the non-paraxial pupil function of a high-NA objective is presented. MTF degradations caused by the non-paraxial diffraction effect are analyzed for on-axial imaging of a far-infrared objective and aberration-free ellipsoidal mirror system. The ellipsoidal mirror system has the same paraxial specifications as the far-infrared objective.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.239-252
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• 2002

A sort sequence $S_n$ is sequence of all unordered pairs of indices in $I_n$={1,2,…n}. With a sort sequence $S_n$ = ($s_1,S_2,...,S_{\frac{n}{2}}$),one can associate a predictive sorting algorithm A($S_n$). An execution of the a1gorithm performs pairwise comparisons of elements in the input set X in the order defined by the sort sequence $S_n$ except that the comparisons whose outcomes can be inferred from the results of the preceding comparisons are not performed. A sort sequence is said to be extremal if it maximizes a given objective function. First we consider the extremal sort sequences with respect to the objective function $\omega$($S_n$) - the expected number of tractive predictions in $S_n$. We study $\omega$-extremal sort sequences in terms of their prediction vectors. Then we consider the objective function $\Omega$($S_n$) - the minimum number of active predictions in $S_n$ over all input orderings.

• Structural Engineering and Mechanics
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• v.14 no.2
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• pp.223-236
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• 2002

The main objective of the present paper is to address a formal procedure for orthotropic steel plates design. The theme of the proposed approach is to recast the design procedure into a mathematical programming model. The objective function to be optimized is the total weight of the structure. The total weight is function of its layout parameters and structural element design variables. Mean while the proposed approach takes into consideration the strength and rigidity criteria in addition to other dimensional constraints. A nonlinear programming model is developed which consists of a nonlinear objective function and a set of implicit/explicit nonlinear constraints. A transformation method is adopted for minimization strategy, where the primal model constrained problem is transformed into a sequence of unconstrained minimization models. The search strategy is based on the well-known Fletcher/Powell algorithm. The finite element technique is adopted for discretization and analysis strategies. Mindlin theory is selected to simulate the finite element model and a selective reduced integration scheme is exploited to avoid a shear lock problem.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.2
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• pp.151-156
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• 2008

It is necessary to perform the research works on the general structural designs and optimum structural designs of double hull tankers and bulk carriers due to the newly built Common Structural Rules(CSR). In this study, an optimum structural design of a mid-ship part of double hull oil tanker was carried out by using the CSR. An optimum structural design program was developed by using the Pareto optimal based multi-objective function method. The hull weight and fabrication cost obtained by the single and multi-objective function methods were compared with existing ship by the consideration of CSR and material cost which is recently increasing.

• Journal of the korean Society of Automotive Engineers
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• v.15 no.1
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• pp.81-88
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• 1993

A direct treatment of the min-max type objective function of the dynamic response optimization problem is proposed. Previously, the min-max type objective function was transformed to an artificial design variable and an additional point-wise state variable constraint function was imposed, which increased the complexity of the optimization problem. Especially, the design sensitivity analysis for the augmented Lagrangian functional with the suggested treatment is established by using the adjoint variable method and a computer program to implement the proposed algorithm is developed. The optimization result of the proposed treatment are obtained for three typical problems and compared with those of the previous treatment. It is concluded that the suggested treatment in much more efficient in the computational effort than the previous treatment with giving the similar optimal solutions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.517-523
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• 2011

A lot of DSM (Demand Side Management) programs have been implemented to promote the effective utilization of resources and the rational development of power industry, and various economic analyses and policy-based studies on DSM have been executed to determine effective subsidy budget. In this paper, a new objective function for deciding an optimal incentive allocation among various programs is presented by introducing the maximization of the total saving power of the programs. For simplicity, the objective function and the constraints is linearized to apply LP(Linear Programming) method. LP program based on Simplex Method was developed by MATLAB. An optimal incentive allocation of 4 DSM programs is presented by the use of the developed MATLAB program.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.464-469
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

• Journal of Power Electronics
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• v.19 no.1
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• pp.168-178
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• 2019

Discrete space vector modulation (DSVM) is an effective method to improve the steady-state performance of the finite control set predictive control for permanent magnet synchronous motor drive systems. However, it requires complex computations due to the presence of numerous virtual voltage vectors. This paper proposes an improved finite control set model-free predictive control using DSVM to reduce the computational burden. First, model-free deadbeat current control is used to generate the reference voltage vector. Then, based on the principle that the voltage vector closest to the reference voltage vector minimizes the cost function, the optimal voltage vector is obtained in an effective way which avoids evaluation of the cost function. Additionally, in order to implement double-objective control, a two-level decisional cost function is designed to sequentially reduce the stator currents tracking error and the inverter switching frequency. The effectiveness of the proposed control is validated based on experimental tests.