• Title/Summary/Keyword: support optimization

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Response Surface Approximation for Fatigue Life Prediction and Its Application to Compromise Decision Support Problem (피로수명예측을 위한 반응표면근사화와 절충의사결정문제의 응용)

  • Baek, Seok-Heum;Cho, Seok-Swoo;Jang, Deuk-Yul;Joo, Won-Sik
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.1187-1192
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    • 2008
  • In this paper, a versatile multi-objective optimization concept for fatigue life prediction is introduced. Multi-objective decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

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Lightweight Crane Design by Using Topology and Shape Optimization (위상최적설계와 형상최적설계를 이용한 크레인의 경량설계)

  • Kim, Young-Chul;Hong, Jung-Kie;Jang, Gang-Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.7
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    • pp.821-826
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    • 2011
  • CAE-based structural optimization techniques are applied for the design of a lightweight crane. The boom of the crane is designed by shape optimization with the shape of the cross section of the boom as the design variable. The design objective is mass minimization, and the static strength and dynamic stiffness of the system are set as the design constraints. Hyperworks, a commercial analysis and optimization software, is used for shape and topology optimization. In order to consistently change the shape of the elements of the boom with respect to the change in the shape of its cross section, the morphing function in Hyperworks is used. The support of the boom of the original model is simplified to model the design domain for topology optimization, which is discretized by using three-dimensional solid elements. The final result after shape and topology optimization is 19% and 17% reduction in the masses of the boom and support, respectively, without a deterioration in the system stiffness.

Short-term Reactive Power Reserve Optimization Based on Trajectory Sensitivity

  • Sun, Quancai;Cheng, Haozhong;Zhang, Jian;Li, Baiqing;Song, Yue
    • Journal of Electrical Engineering and Technology
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    • v.12 no.2
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    • pp.541-548
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    • 2017
  • An increasing concern is paid to short-term voltage stability with the growth of penetration of induction motor loads. Reactive power reserve(RPR) of power system is critical to improve voltage stability. A definition of short-term voltage stability-related RPR(SVRPR) is proposed. Generators vary their contributions to voltage stability with their location and system condition, etc. Voltage support coefficient based on the second-order trace sensitivity method is proposed to evaluate SVRPR's contribution to short-term voltage stability. The evaluation method can account for the generator's reactive support in transient process and the contingency severity. Then an optimization model to improve short-term voltage stability is built. To deal with multiple contingencies, contingency weight taking into account both its probability and severity is proposed. The optimization problem is solved by primal dual interior point method. Testing on IEEE_39 bus system, it is indicated that the method proposed is effective. Short-term voltage stability is improved significantly by the way of SVRPR optimization. Hence, the approach can be used to prevent the happening of voltage collapse during system's contingency.

Efficient Sign Language Recognition and Classification Using African Buffalo Optimization Using Support Vector Machine System

  • Karthikeyan M. P.;Vu Cao Lam;Dac-Nhuong Le
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.8-16
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    • 2024
  • Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

Design Optimization of Valve Support with Enhanced Seismic Performance (내진성능 향상을 위한 밸브지지대 최적형상 설계)

  • Kim, Hyoung Eun;Keum, Dong Yeop;Kim, Dea Jin;Kim, Jun Ho;Hong, Seong Kyeong;Choi, Won Mok;Kim, Sang Yeong;Seok, Chang Seong
    • Journal of the Korean Society for Precision Engineering
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    • v.32 no.11
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    • pp.997-1005
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    • 2015
  • In this study, modal analysis and equivalent static load analysis for valve supports of 26" gas piping in gas stations were conducted and the existing straight and inclined types of valve supports were compared using seismic performance testing. Also, a new valve support shape was suggested by optimizing position of fastener holes, width and thickness of the support, and size of bracket. Improvement in seismic performance by design optimization was verified through equivalent static load analysis. The seismic performance of the newly proposed valve support was greatly improved and the maximum displacement and maximum stress of the seismic load was about 20% lower than those of the existing valve support.

A New Support Vector Machine Model Based on Improved Imperialist Competitive Algorithm for Fault Diagnosis of Oil-immersed Transformers

  • Zhang, Yiyi;Wei, Hua;Liao, Ruijin;Wang, Youyuan;Yang, Lijun;Yan, Chunyu
    • Journal of Electrical Engineering and Technology
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    • v.12 no.2
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    • pp.830-839
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    • 2017
  • Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

Dynamic Response Optimization of a Mobile Harbor Crane with a Moving Support (지지부가 움직이는 모바일하버용 크레인의 동적 응답 최적설계)

  • Kim, Hyun-Bum;Lee, Jae-Jun;Jang, Hwan-Hak;Park, Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.5
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    • pp.497-504
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    • 2012
  • The mobile harbor is a new innovative system that delivers containers from a containership to a harbor without good infrastructure. A crane is installed on the deck of the mobile harbor and transfers the containers. The structure of the crane is influenced by the inertia force that occurs from a moving support. Thus an accurate safety verification considering the moving support is required. Lightweight of the crane structure is also significant in the design for low production cost and efficient operation. Dynamic response optimization can be exploited to achieve these two requirements. Equivalent static loads method is employed for dynamic response optimization of the crane. The equivalent static loads method transforms dynamic loads to equivalent static loads, and static response structural optimization with the transformed equivalent static loads are solved. The process proceeds in a cyclic manner. A new method is proposed to consider the moving supports and the structure of the mobile harbor is optimized using the proposed method.

Optimum Allocation of Pipe Support Using Combined Optimization Algorithm by Genetic Algorithm and Random Tabu Search Method (유전알고리즘과 Random Tabu 탐색법을 조합한 최적화 알고리즘에 의한 배관지지대의 최적배치)

  • 양보석;최병근;전상범;김동조
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.3
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    • pp.71-79
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    • 1998
  • This paper introduces a new optimization algorithm which is combined with genetic algorithm and random tabu search method. Genetic algorithm is a random search algorithm which can find the global optimum without converging local optimum. And tabu search method is a very fast search method in convergent speed. The optimizing ability and convergent characteristics of a new combined optimization algorithm is identified by using a test function which have many local optimums and an optimum allocation of pipe support. The caculation results are compared with the existing genetic algorithm.

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Fast Training of Structured SVM Using Fixed-Threshold Sequential Minimal Optimization

  • Lee, Chang-Ki;Jang, Myung-Gil
    • ETRI Journal
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    • v.31 no.2
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    • pp.121-128
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    • 2009
  • In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for structured SVM problems. FSMO is conceptually simple, easy to implement, and faster than the standard support vector machine (SVM) training algorithms for structured SVM problems. Because FSMO uses the fact that the formulation of structured SVM has no bias (that is, the threshold b is fixed at zero), FSMO breaks down the quadratic programming (QP) problems of structured SVM into a series of smallest QP problems, each involving only one variable. By involving only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection. For the various test sets, FSMO is as accurate as an existing structured SVM implementation (SVM-Struct) but is much faster on large data sets. The training time of FSMO empirically scales between O(n) and O($n^{1.2}$), while SVM-Struct scales between O($n^{1.5}$) and O($n^{1.8}$).

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Optimal locations of point supports in laminated rectangular plates for maximum fundamental frequency

  • Wang, C.M.;Xiang, Y.;Kitipornchai, S.
    • Structural Engineering and Mechanics
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    • v.5 no.6
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    • pp.691-703
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    • 1997
  • This paper investigates the optimal locations of internal point supports in a symmetric crossply laminated rectangular plate for maximum fundamental frequency of vibration. The method used for solving this optimization problem involves the Rayleigh-Ritz method for the vibration analysis and the simplex method of Nelder and Mead for the iterative search of the optimum support locations. Being a continuum method, the Rayleigh-Ritz method allows easy handling of the changing point support locations during the optimization search. Rectangular plates of various boundary conditions, aspect ratios, composed of different numbers of layers, and with one, two and three internal point supports are analysed. The interesting results on the optimal locations of the point supports showed that (a) there are multiple solutions; (b) the locations are dependent on both the plate aspect ratios and the number of layers (c) the fundamental frequency may be raised significantly with appropriate positioning of the point supports.