• Computational Structural Engineering
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• v.24 no.3
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• pp.26-32
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• 2011

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1260-1283
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• 2019

Low earth orbit (LEO) satellite broadband network is a crucial part of the space information network. LEO satellite constellation design is a top-level design, which plays a decisive role in the overall performance of the LEO satellite network. However, the existing works on constellation design mainly focus on the coverage criterion and rarely take network performance into the design process. In this article, we develop a unified framework for constellation optimization design in LEO satellite broadband networks. Several design criteria including network performance and coverage capability are combined into the design process. Firstly, the quality of service (QoS) metrics is presented to evaluate the performance of the LEO satellite broadband network. Also, we propose a network stability model for the rapid change of the satellite network topology. Besides, a mathematical model of constellation optimization design is formulated by considering the network cost-efficiency and stability. Then, an optimization algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is provided for the problem of constellation design. Finally, the proposed method is further evaluated through numerical simulations. Simulation results validate the proposed method and show that it is an efficient and effective approach for solving the problem of constellation design in LEO satellite broadband networks.

• Computers and Concrete
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• v.17 no.5
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• pp.629-638
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• 2016

Optimization of the concrete mixture design is a process of search for a mixture for which the sum of the cost of the ingredients is the lowest, yet satisfying the required performance of concrete. In this study, a statistical model was carried out to model a cost effective optimal mix proportioning of high strength self-compacting concrete (HSSCC) using the Response Surface Methodology (RSM). The effect of five key mixture parameters such as water-binder ratio, cement content, fine aggregate percentage, fly ash content and superplasticizer content on the properties and performance of HSSCC like compressive strength, passing ability, segregation resistance and manufacturing cost were investigated. To demonstrate the responses of model in quadratic manner Central Composite Design (CCD) was chosen. The statistical model showed the adjusted correlation coefficient R2adj values were 92.55%, 93.49%, 92.33%, and 100% for each performance which establish the adequacy of the model. The optimum combination was determined to be $439.4kg/m^3$ cement content, 35.5% W/B ratio, 50.0% fine aggregate, $49.85kg/m^3$ fly ash, and $7.76kg/m^3$ superplasticizer within the interest region using desirability function. Finally, it is concluded that multiobjective optimization method based on desirability function of the proposed response model offers an efficient approach regarding the HSSCC mixture optimization.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.11
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• pp.973-981
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• 2013

The main role of an acoustic diffuser is to diffuse reflected sound field spatially. Since the pioneering work of Schroeder, there have been investigations to improve its performance by using shape/sizing optimization methods. In this paper, a gradient-based topology optimization algorithm is newly presented to find the optimal distribution of reflecting materials for maximizing diffuser performance. Time-harmonic acoustic analysis in a two-dimensional acoustic domain is carried out where the domain is discretized by finite elements. Perfectly matched layers are placed to surround the domain to simulate non-reflecting boundary conditions. Design variables are assigned to each element of which material properties are interpolated between those of air and those of a rigid body. An approach to extract the reflected field from the total acoustic field is employed. To validate the effectiveness of the proposed method, design problems are solved at different frequencies. The performance of the optimized diffusers obtained by the proposed method is compared against that of the conventional Schroeder diffusers.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.741-743
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• 2003

A reliability-based topology optimization (RBTO) for electromagnetic systems using the finite element method is presented. Permeability and applied current density are considered as uncertain variable. In order to compute reliability constraints, performance measure approach is used. To find the reliability index, the limit state function is linearly approximated at each iteration. Numerical examples show the effectiveness of the proposed method.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.136-147
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• 2003

To achieve an optimal performance for a given problem, we need an integrative process of the parameter optimization via learning and the structure optimization via model selection. In this paper, we propose an efficient optimization method for improving generalization performance by considering the property of each sub-method and by combining them with common theoretical properties. First, weight parameters are optimized by natural gradient teaming with adaptive regularization, which uses a diverse error function. Second, the network structure is optimized by eliminating unnecessary parameters with natural pruning. Through iterating these processes, candidate models are constructed and evaluated based on the Bayesian Information Criterion so that an optimal one is finally selected. Through computational experiments on benchmark problems, we confirm the weight parameter and structure optimization performance of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.1-8
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• 2007

In this paper, research on joint optimization of the image spatial registration and the exposure compensation is conducted. The exposure compensation is performed in a frame work of the intensity compensation based on the polynomial approximation of the relationship between images. This compensation is jointly combined with the registration problem employing the Gauss-Newton nonlinear optimization method. In this paper, to perform for a simple and stable optimization, the block-coordinate method is combined with the Gauss-Newton optimization and extensively compared with the traditional approaches. Furthermore, regression analysis is considered in the compensation part for a better stable performance. By combining the block-coordinate method with the Gauss-Newton optimization, we can obtain a compatible performance reducing the computational complexity and stabilizing the performance. In the numerical result for a particular image, we obtain a satisfactory result for 10 repeats of the iteration, which implies a 50% reduction of the computational complexity. The error is also further reduced by 1.5dB compared to the ordinary method.

• Smart Structures and Systems
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• v.26 no.1
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• pp.49-61
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• 2020

This paper proposes a novel high performance vibration control device, multiple tuned mass dampers-inerters (MTMDI), to suppress the oscillatory motions of structures. The MTMDI, similar to the MTMD, involves multiple tuned mass damper-inerter (TMDI) units. In order to reveal the basic performance of the MTMDI, it is installed on a single degree-of-freedom (SDOF) structure excited by the ground acceleration, and the dynamic magnification factors (DMF) of the structure-MTMDI system are formulated. The optimization criterion is determined as the minimization of maximum values of the relative displacement's DMF for the controlled structure. Based on the particle swarm optimization (PSO) algorithm to tune the optimum parameters of the MTMDI, its performance has been investigated and evaluated in terms of control effectiveness, strokes, stiffness and damping coefficient, inerter element force, and robustness in frequency domain. Meanwhile, further comparison between the MTMDI with MTMD has been conducted. Numerical results clearly demonstrate the MTMDI outperforms the MTMD in control effectiveness and strokes of mass blocks. Additionally, in the aspects of frequency perturbations on both earthquake excitations and structures, the robustness of the MTMDI is also better than the MTMD.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.415-424
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• 2004

In this paper, we introduce and investigate a new category of rule-based fuzzy inference system based on Information Granulation(IG). The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of “If..., then...” statements, and exploits the theory of system optimization and fuzzy implication rules. The form of the fuzzy rules comes with three types of fuzzy inferences: a simplified one that involves conclusions that are fixed numeric values, a linear one where the conclusion part is viewed as a linear function of inputs, and a regression polynomial one as the extended type of the linear one. By the nature of the rule-based fuzzy systems, these fuzzy models are geared toward capturing relationships between information granules. The form of the information granules themselves becomes an important design features of the fuzzy model. Information granulation with the aid of HCM(Hard C-Means) clustering algorithm hell)s determine the initial parameters of rule-based fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial function being used in the Premise and consequence Part of the fuzzy rules. And then the initial Parameters are tuned (adjusted) effectively with the aid of the improved complex method(ICM) and the standard least square method(LSM). In the sequel, the ICM and LSM lead to fine-tuning of the parameters of premise membership functions and consequent polynomial functions in the rules of fuzzy model. An aggregate objective function with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.493-502
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• 2021

A Vegetative Propagation by Runner(VPR) Algorithm-based on MPPT Algorithm that can track MPP by adapting to external environmental changes is presented. VPR is an optimization algorithm that mimics the plant ecology of movement and reproduction based on vegetation organs. The VPR algorithm includes a procedure for aging and a procedure for searching the surroundings by rhizomes. Accordingly, it is possible to continuously search around the optimal point. Therefore, the VPR-based MPPT algorithm can continuously search for an optimal point by adapting the changes in the external environment in the process of executing the MPPT algorithm. In this paper, we analyzed the performance of the VPR-based MPPT algorithm by a number of simulations. In addition, the superiority of performance was compared by performance comparison in the same environment as MPPT algorithm based on PSO.