• 제목/요약/키워드: Multilevel Method

검색결과 294건 처리시간 0.028초

메타모델 기반 다단계 최적설계에 대한 순차적 알고리듬 (A Sequential Algorithm for Metamodel-Based Multilevel Optimization)

  • 김강민;백석흠;홍순혁;조석수;주원식
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.1198-1203
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    • 2008
  • An efficient sequential optimization approach for metamodel was presented by Choi et al [6]. This paper describes a new approach of the multilevel optimization method studied in Refs. [5] and [21-25]. The basic idea is concerned with multilevel iterative methods which combine a descent scheme with a hierarchy of auxiliary problems in lower dimensional subspaces. After fitting a metamodel based on an initial space filling design, this model is sequentially refined by the expected improvement criterion. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to understand and use. As a check on effectiveness, the proposed method is applied to a classical cantilever beam.

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An Improved Multilevel Fuzzy Comprehensive Evaluation to Analyse on Engineering Project Risk

  • LI, Xin;LI, Mufeng;HAN, Xia
    • 융합경영연구
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    • 제10권5호
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    • pp.1-6
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    • 2022
  • Purpose: To overcome the question that depends too much on expert's subjective judgment in traditional risk identification, this paper structure the multilevel generalized fuzzy comprehensive evaluation mathematics model of the risk identification of project, to research the risk identification of the project. Research design, data and methodology: This paper constructs the multilevel generalized fuzzy comprehensive evaluation mathematics model. Through iterative algorithm of AHP analysis, make sure the important degree of the sub project in risk analysis, then combine expert's subjective judgment with objective quantitative analysis, and distinguish the risk through identification models. Meanwhile, the concrete method of multilevel generalized fuzzy comprehensive evaluation is probed. Using the index weights to analyse project risks is discussed in detail. Results: The improved fuzzy comprehensive evaluation algorithm is proposed in the paper, at first the method of fuzzy sets core is used to optimize the fuzzy relation matrix. It improves the capability of the algorithm. Then, the method of entropy weight is used to establish weight vectors. This makes the computation process fair and open. And thereby, the uncertainty of the evaluation result brought by the subjectivity can be avoided effectively and the evaluation result becomes more objective and more reasonable. Conclusions: In this paper, we use an improved fuzzy comprehensive evaluation method to evaluate a railroad engineering project risk. It can give a more reliable result for a reference of decision making.

A CLASS OF MULTILEVEL RECURSIVE INCOMPLETE LU PRECONDITIONING TECHNIQUES

  • Zhang, Jun
    • Journal of applied mathematics & informatics
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    • 제8권2호
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    • pp.305-326
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    • 2001
  • We introduce a class of multilevel recursive incomplete LU preconditioning techniques (RILUM) for solving general sparse matrices. This techniques is based on a recursive two by two block incomplete LU factorization on the coefficient martix. The coarse level system is constructed as an (approximate) Schur complement. A dynamic preconditioner is obtained by solving the Schur complement matrix approximately. The novelty of the proposed techniques is to solve the Schur complement matrix by a preconditioned Krylov subspace method. Such a reduction process is repeated to yield a multilevel recursive preconditioner.

Analysis of Cascaded H-Bridge Multilevel Inverter in DTC-SVM Induction Motor Drive for FCEV

  • Gholinezhad, Javad;Noroozian, Reza
    • Journal of Electrical Engineering and Technology
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    • 제8권2호
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    • pp.304-315
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    • 2013
  • In this paper, analysis of cascaded H-bridge multilevel inverter in DTC-SVM (Direct Torque Control-Space Vector Modulation) based induction motor drive for FCEV (Fuel Cell Electric Vehicle) is presented. Cascaded H-bridge multilevel inverter uses multiple series units of H-bridge power cells to achieve medium-voltage operation and low harmonic distortion. In FCEV, a fuel cell stack is used as the major source of electric power moreover the battery and/or ultra-capacitor is used to assist the fuel cell. These sources are suitable for utilizing in cascaded H-bridge multilevel inverter. The drive control strategy is based on DTC-SVM technique. In this scheme, first, stator voltage vector is calculated and then realized by SVM method. Contribution of multilevel inverter to the DTC-SVM scheme is led to achieve high performance motor drive. Simulations are carried out in Matlab-Simulink. Five-level and nine-level inverters are applied in 3hp FCEV induction motor drive for analysis the multilevel inverter. Each H-bridge is implemented using one fuel cell and battery. Good dynamic control and low ripple in the torque and the flux as well as distortion decrease in voltage and current profiles, demonstrate the great performance of multilevel inverter in DTC-SVM induction motor drive for vehicle application.

Predictive Current Control for Multilevel Cascaded H-Bridge Inverters Based on a Deadbeat Solution

  • Qi, Chen;Tu, Pengfei;Wang, Peng;Zagrodnik, Michael
    • Journal of Power Electronics
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    • 제17권1호
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    • pp.76-87
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    • 2017
  • Finite-set predictive current control (FS-PCC) is advantageous for power converters due to its high dynamic performance and has received increasing interest in multilevel inverters. Among multilevel inverter topologies, the cascaded H-bridge (CHB) inverter is popular and mature in the industry. However, a main drawback of FS-PCC is its large computational burden, especially for the application of CHB inverters. In this paper, an FS-PCC method based on a deadbeat solution for three-phase zero-common-mode-voltage CHB inverters is proposed. In the proposed method, an inverse model of the load is utilized to calculate the reference voltage based on the reference current. In addition, a cost function is directly expressed in the terms of the voltage errors. An optimal control actuation is selected by minimizing the cost function. In the proposed method, only three instead of all of the control actuations are used for the calculations in one sampling period. This leads to a significant reduction in computations. The proposed method is tested on a three-phase 5-level CHB inverter. Simulation and experimental results show a very similar and comparable control performance from the proposed method compared with the traditional FS-PCC method which evaluates the cost function for all of the control actuations.

Statistical Method for Implementing the Experimenter Effect in the Analysis of Gene Expression Data

  • Kim, In-Young;Rha, Sun-Young;Kim, Byung-Soo
    • Communications for Statistical Applications and Methods
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    • 제13권3호
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    • pp.701-718
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    • 2006
  • In cancer microarray experiments, the experimenter or patient which is nested in each experimenter often shows quite heterogeneous error variability, which should be estimated for identifying a source of variation. Our study describes a Bayesian method which utilizes clinical information for identifying a set of DE genes for the class of subtypes as well as assesses and examines the experimenter effect and patient effect which is nested in each experimenter as a source of variation. We propose a Bayesian multilevel mixed effect model based on analysis of covariance (ANACOVA). The Bayesian multilevel mixed effect model is a combination of the multilevel mixed effect model and the Bayesian hierarchical model, which provides a flexible way of defining a suitable correlation structure among genes.

Carrier Based Single-State PWM Technique for Minimizing Vector Errors in Multilevel Inverters

  • Nho, Nguyen Van;Hai, Quach Thanh;Lee, Hong-Hee
    • Journal of Power Electronics
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    • 제10권4호
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    • pp.357-364
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    • 2010
  • In this paper, a novel analysis of a carrier based PWM method for multilevel inverters is presented. The space vector PWM and carrier based PWM correlations in multilevel inverters are investigated in a nominal two-level switching diagram. The obtained results can be applied to design various carrier PWM techniques. In this paper, a carrier based single-state PWM technique, which reduces the switching number and optimizes the active voltage errors, is presented. This PWM technique can be advantageous if there are a large number of levels. The proposed method is mathematically formulated and demonstrated by simulations and experimental results.

How do multilevel privacy controls affect utility-privacy trade-offs when used in mobile applications?

  • Kim, Seung-Hyun;Ko, In-Young
    • ETRI Journal
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    • 제40권6호
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    • pp.813-823
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    • 2018
  • In existing mobile computing environments, users need to choose between their privacy and the services that they can receive from an application. However, existing mobile platforms do not allow users to perform such trade-offs in a fine-grained manner. In this study, we investigate whether users can effectively make utility-privacy trade-offs when they are provided with a multilevel privacy control method that allows them to recognize the different quality of service that they will receive from an application by limiting the disclosure of their private information in multiple levels. We designed a research model to observe users' utility-privacy trade-offs in accordance with the privacy control methods and other factors such as the trustworthiness of an application, quality level of private information, and users' privacy preferences. We conducted a user survey with 516 participants and found that, compared with the existing binary privacy controls, both the service utility and the privacy protection levels were significantly increased when the users used the multilevel privacy control method.

Performance Analysis of a Novel Reduced Switch Cascaded Multilevel Inverter

  • Nagarajan, R.;Saravanan, M.
    • Journal of Power Electronics
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    • 제14권1호
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    • pp.48-60
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    • 2014
  • Multilevel inverters have been widely used for high-voltage and high-power applications. Their performance is greatly superior to that of conventional two-level inverters due to their reduced total harmonic distortion (THD), lower switch ratings, lower electromagnetic interference, and higher dc link voltages. However, they have some disadvantages such as an increased number of components, a complex pulse width modulation control method, and a voltage-balancing problem. In this paper, a novel nine-level reduced switch cascaded multilevel inverter based on a multilevel DC link (MLDCL) inverter topology with reduced switching components is proposed to improve the multilevel inverter performance by compensating the above mentioned disadvantages. This topology requires fewer components when compared to diode clamped, flying capacitor and cascaded inverters and it requires fewer carrier signals and gate drives. Therefore, the overall cost and circuit complexity are greatly reduced. This paper presents modulation methods by a novel reference and multicarrier based PWM schemes for reduced switch cascaded multilevel inverters (RSCMLI). It also compares the performance of the proposed scheme with that of conventional cascaded multilevel inverters (CCMLI). Simulation results from MATLAB/SIMULINK are presented to verify the performance of the nine-level RSCMLI. Finally, a prototype of the nine-level RSCMLI topology is built and tested to show the performance of the inverter through experimental results.

Determining the adjusting bias in reactor pressure vessel embrittlement trend curve using Bayesian multilevel modelling

  • Gyeong-Geun Lee;Bong-Sang Lee;Min-Chul Kim;Jong-Min Kim
    • Nuclear Engineering and Technology
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    • 제55권8호
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    • pp.2844-2853
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    • 2023
  • A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs). For multilevel model development, the Baseline 22 surveillance dataset was basically classified into groups based on the NPP name, product form, and notch orientation. By including the notch direction in the grouping criteria, the developed model could account for TTS differences among NPP groups with different notch orientations, which have not been considered in previous ETCs. The parameters of the multilevel model and biases of the NPP groups were calculated using the Markov Chain Monte Carlo method. As the number of data points within a group increased, the group bias approached the mean residual, resulting in reduced credible intervals of the mean, and vice versa. Even when the number of surveillance test data points was less than three, the multilevel model could estimate appropriate biases without overfitting. The model also allowed for a quantitative estimate of the changes in the bias and prediction interval that occurred as a result of adding more surveillance test data. The biases estimated through the multilevel model significantly improved the performance of E900-15.