• Title/Summary/Keyword: engineering optimization

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Parameter optimization for SVM using dynamic encoding algorithm

  • Park, Young-Su;Lee, Young-Kow;Kim, Jong-Wook;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2542-2547
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    • 2005
  • In this paper, we propose a support vector machine (SVM) hyper and kernel parameter optimization method which is based on minimizing radius/margin bound which is a kind of estimation of leave-one-error. This method uses dynamic encoding algorithm for search (DEAS) and gradient information for better optimization performance. DEAS is a recently proposed optimization algorithm which is based on variable length binary encoding method. This method has less computation time than genetic algorithm (GA) based and grid search based methods and better performance on finding global optimal value than gradient based methods. It is very efficient in practical applications. Hand-written letter data of MNI steel are used to evaluate the performance.

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Reliability-Based Design Optimization of a Superconducting Magnetic Energy Storage System (SMES) Utilizing Reliability Index Approach

  • Jeung, Gi-Woo;Kim, Dong-Wook;Sung, Young-Hwa;Kim, Heung-Geun;Kim, Dong-Hun
    • Journal of Magnetics
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    • v.17 no.1
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    • pp.46-50
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    • 2012
  • A reliability-based optimization method for electromagnetic design is presented to take uncertainties of design parameters into account. The method can provide an optimal design satisfying a specified confidence level in the presence of uncertain parameters. To achieve the goal, the reliability index approach based on the firstorder reliability method is adopted to deal with probabilistic constraint functions and a double-loop optimization algorithm is implemented to obtain an optimum. The proposed method is applied to the TEAM Workshop Problem 22 and its accuracy and efficiency is verified with reference of Monte Carlo simulation results.

Transceiver Optimization for the Multi-Antenna Downlink in MIMO Cognitive System

  • Zhu, Wentao;Yang, Jingbo;Jia, Tingting;Liu, Xu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.12
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    • pp.5015-5027
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    • 2015
  • Transceiver optimization in multiple input multiple output (MIMO) cognitive systems is studied in this paper. The joint transceiver beamformer design is introduced to minimize the transmit power at secondary base station (SBS) while simultaneously controlling the interference to primary users (PUs) and satisfying the secondary users (SUs) signal-to-interference-plus-noise ratio (SINR) based on the convex optimization method. Due to the limited cooperation between SBS and PUs, the channel state information (CSI) usually cannot be obtained perfectly at the SBS in cognitive system. In this study, both perfect and imperfect CSI scenarios are considered in the beamformer design, and the proposed method is robust to CSI error. Numerical results validate the effectiveness of the proposed algorithm.

Sidelobe Level Optimization of Microstrip Patch Array using Genetic Algorithms (유전자 알고리즘을 이용한 마이크로스트립 패치 배열 안테나의 부엽레벨 최적화)

  • Kim, Dong-Hyun;Kim, Young-Sik
    • Proceedings of the Korea Electromagnetic Engineering Society Conference
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    • 2003.11a
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    • pp.428-431
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    • 2003
  • In this paper, distances between elements are optimized for low sidelobe level (SLL) microstrip patch array using Genetic Algorithms. Genetic Algorithms are "global" numerical-optimization methods, it's advantages are very simple coding and fast optimization. This paper show how to optimize the maximum SLL using Genetic Algorithms. In the results, although mutual coupling is neglected, it's maximum SLL is 3.5 dB lower than Uniformly Spaced Array(distance=$0.5{\lambda}$).

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Genetic Algorithm Based Design Optimization of a Six Phase Induction Motor

  • Fazlipour, Z.;Kianinezhad, R.;Razaz, M.
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1007-1014
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    • 2015
  • An optimally designed six-phase induction motor (6PIM) is compared with an initial design induction motor having the same ratings. The Genetic Algorithm (GA) method is used for optimization and multi objective function is considered. Comparison of the optimum design with the initial design reveals that better performance can be obtained by a simple optimization method. Also in this paper each design of 6PIM, is simulated by MAXWELL_2D. The obtained simulation results are compared in order to find the most suitable solution for the specified application, considering the influence of each design upon the motor performance. Construction a 6PIM based on the information obtained from GA method has been done. Quality parameters of the designed motors, such as: efficiency, power losses and power factor measured and optimal design has been evaluated. Laboratory tests have proven the correctness of optimal design.

Topology optimization of reinforced concrete structure using composite truss-like model

  • Yang, Zhiyi;Zhou, Kemin;Qiao, Shengfang
    • Structural Engineering and Mechanics
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    • v.67 no.1
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    • pp.79-85
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    • 2018
  • Topology optimization of steel and concrete composite based on truss-like material model is studied in this paper. First, the initial design domain is filled with concrete, and the steel is distributed in it. The problem of topology optimization is to minimize the volume of steel material and solved by full stress method. Then the optimized steel and concrete composite truss-like continuum is obtained. Finally, the distribution of steel material is determined based on the optimized truss-like continuum. Several numerical results indicate the numerical instability and rough boundary are settled. And more details of manufacture and construction can be presented based on the truss-like material model. Hence, the truss-like material model of steel and concrete is efficient to establish the distribution of steel material in concrete.

Coupling Particles Swarm Optimization for Multimodal Electromagnetic Problems

  • Pham, Minh-Trien;Song, Min-Ho;Koh, Chang-Seop
    • Journal of Electrical Engineering and Technology
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    • v.5 no.3
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    • pp.423-430
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    • 2010
  • Particle swarm optimization (PSO) algorithm is designed to find a single global optimal point. However, the PSO needs to be modified in order to find multiple optimal points of a multimodal function. These modifications usually divide a swarm of particles into multiple subswarms; in turn, these subswarms try to find their own optimal point, resulting in multiple optimal points. In this work, we present a new PSO algorithm, called coupling PSO to find multiple optimal points of a multimodal function based on coupling particles. In the coupling PSO, each main particle may generate a new particle to form a couple, after which the couple searches its own optimal point using non-stop-moving PSO algorithm. We tested the suggested algorithm and other ones, such as clustering PSO and niche PSO, over three analytic functions. The coupling PSO algorithm was also applied to solve a significant benchmark problem, the TEAM workshop problem 22.

Optimization of an Electron Microwave Oven Window Injection Mold Using Kriging Based Approximation Model (크리깅을 이용한 전자 오븐 윈도우 부품용 사출금형의 최적설계)

  • Ryu M. R.;Lee K. H.;Kim Y. H.;Park H. S.
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.7 s.172
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    • pp.177-184
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    • 2005
  • Recently, the engineering designer of injection mould has become more and more dependent on the CAE. In the design factors of injection mould, the shrinkage rate should be considered as one of the important performances to produce the reliable products. therefore the shrinkage rate can be mostly calculated by the MoldFlow and Pro-engineering. in the design process. However it is not easy to predict the shrinkage rate of a plastic injection mold in its design process because the analysis can take minutes to hours, the high computational costs of performing the analysis limit their use in design optimization. In this study, the surrogate models, DACE model, based on the Kriging in order to optimize the shrinkage rate of electric microwave oven window is used in lieu of the original models, facilitating design optimization.

Robust design of liquid column vibration absorber in seismic vibration mitigation considering random system parameter

  • Debbarma, Rama;Chakraborty, Subrata
    • Structural Engineering and Mechanics
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    • v.53 no.6
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    • pp.1127-1141
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    • 2015
  • The optimum design of liquid column dampers in seismic vibration control considering system parameter uncertainty is usually performed by minimizing the unconditional response of a structure without any consideration to the variation of damper performance due to uncertainty. However, the system so designed may be sensitive to the variations of input system parameters due to uncertainty. The present study is concerned with robust design optimization (RDO) of liquid column vibration absorber (LCVA) considering random system parameters characterizing the primary structure and ground motion model. The RDO is obtained by minimizing the weighted sum of the mean value of the root mean square displacement of the primary structure as well as its standard deviation. A numerical study elucidates the importance of the RDO procedure for design of LCVA system by comparing the RDO results with the results obtained by the conventional stochastic structural optimization procedure and the unconditional response based optimization.

Sensing Optimization for an Receiver Structure in Cognitive Radio Systems

  • Kang, Bub-Joo;Nam, Yoon-Seok
    • Journal of information and communication convergence engineering
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    • v.9 no.1
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    • pp.27-31
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    • 2011
  • This paper describes the optimization of spectrum sensing in terms of the throughput of a cognitive radio (CR) system. Dealing with the optimization problem of spectrum sensing, this paper evaluates the throughput of a CR system by considering such situations as the penalty time of a channel search and incumbent user (IU) detection delay caused by a missed detection of an incumbent signal. Also, this paper suggests a serial channel search scheme as the search method for a vacant channel, and derives its mean channel search time by considering the penalty time due to the false alarm of a vacant channel search. The numerical results suggest the optimum sensing time of the channel search process using the derived mean channel search time of a serial channel search in the case of a sensing hardware structure with single radio frequency (RF) path. It also demonstrates that the average throughput is improved by two separate RF paths in spite of the hardware complexity of an RF receiver.