• Title/Summary/Keyword: Approximate

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Comparison of Rigorous Design Procedure with Approximate Design Procedure for Variable Sampling Plans Indexed by Quality Loss

  • Ishii, Yoma;Arizono, Ikuo;Tomohiro, Ryosuke;Takemoto, Yasuhiko
    • Industrial Engineering and Management Systems
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    • v.15 no.3
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    • pp.231-238
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    • 2016
  • Traditional acceptance sampling plans have focused on the proportion of nonconforming items as an attribute criterion for quality. In today's modern quality management under high quality production environments, the reduction of the deviation from a target value in a quality characteristic has become the most important purpose. In consequence, various inspection plans for the purpose of reducing the deviation from the target value in the quality characteristic have been investigated. In this case, a concept of the quality loss evaluated by the deviation from the target value has been accepted as the variable evaluation criterion of quality. Further, some quality measures based on the quality loss have been devised; e.g. the process loss and the process capability index. Then, as one of inspection plans based on the quality loss, the rigorous design procedure for the variable sampling plan having desired operating characteristics (VS-OC plan) indexed by the quality loss has been proposed by Yen and Chang in 2009. By the way, since the estimator of the quality loss obeys the non-central chi-square distribution, the rigorous design procedure for the VS-OC plan indexed by the quality loss is complicated. In particular, the rigorous design procedure for the VS-OC plan requires a large number of the repetitive and complicated numerical calculation about the non-central chi-square distribution. On the other hand, an approximate design procedure for the VS-OC plan has been proposed before the proposal of the above rigorous design procedure. The approximate design procedure for the VS-OC plan has been constructed by combining Patnaik approximation relating the non-central chi-square distribution to the central chi-square distribution and Wilson-Hilferty approximation relating the central chi-square distribution to the standard normal distribution. Then, the approximate design procedure has been devised as a convenient procedure without complicated and repetitive numerical calculations. In this study, through some comparisons between the rigorous and approximate design procedures, the applicability of the approximate design procedure has been confirmed.

Approximate Periods of Strings based on Distance Sum for DNA Sequence Analysis (DNA 서열분석을 위한 거리합기반 문자열의 근사주기)

  • Jeong, Ju Hui;Kim, Young Ho;Na, Joong Chae;Sim, Jeong Seop
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.2
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    • pp.119-122
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    • 2013
  • Repetitive strings such as periods have been studied vigorously in so diverse fields as data compression, computer-assisted music analysis, bioinformatics, and etc. In bioinformatics, periods are highly related to repetitive patterns in DNA sequences so called tandem repeats. In some cases, quite similar but not the same patterns are repeated and thus we need approximate string matching algorithms to study tandem repeats in DNA sequences. In this paper, we propose a new definition of approximate periods of strings based on distance sum. Given two strings $p({\mid}p{\mid}=m)$ and $x({\mid}x{\mid}=n)$, we propose an algorithm that computes the minimum approximate period distance based on distance sum. Our algorithm runs in $O(mn^2)$ time for the weighted edit distance, and runs in O(mn) time for the edit distance, and runs in O(n) time for the Hamming distance.

Probability distribution-based approximation matrix multiplication simplification algorithm (확률분포 생성을 통한 근사 행렬 곱셈 간소화 방법)

  • Kwon, Oh-Young;Seo, Kyoung-Taek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.11
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    • pp.1623-1629
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    • 2022
  • Matrix multiplication is a fundamental operation widely used in science and engineering. There is an approximate matrix multiplication method as a way to reduce the amount of computation of matrix multiplication. Approximate matrix multiplication determines an appropriate probability distribution for selecting columns and rows of matrices, and performs approximate matrix multiplication by selecting columns and rows of matrices according to this distribution. Probability distributions are generated by considering both matrices A and B participating in matrix multiplication. In this paper, we propose a method to generate a probability distribution that selects columns and rows of matrices to be used for approximate matrix multiplication, targeting only matrix A. Approximate matrix multiplication was performed on 1000×1000 ~ 5000×5000 matrices using existing and proposed methods. The approximate matrix multiplication applying the proposed method compared to the conventional method has been shown to be closer to the original matrix multiplication result, averaging 0.02% to 2.34%.

Surrogate Models and Genetic Algorithm Application to Approximate Optimization of Discrete Design for A60 Class Deck Penetration Piece (A60 급 갑판 관통 관의 이산설계 근사최적화를 위한 대리모델과 유전자 알고리즘 응용)

  • Park, Woo Chang;Song, Chang Yong
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.2
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    • pp.377-386
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    • 2021
  • The A60 class deck penetration piece is a fire-resistant system installed on a horizontal compartment to prevent flame spreading and protect lives in fire accidents in ships and offshore plants. This study deals with approximate optimization using discrete variables for the fire resistance design of an A60 class deck penetration piece using different surrogate models and a genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class deck penetration piece. For the approximate optimization of the piece, the length, diameter, material type, and insulation density were applied to discrete design variables, and temperature, productivity, and cost constraints were considered. The approximate optimum design problem based on the surrogate models was formulated such that the discrete design variables were determined by minimizing the weight of the piece subjected to the constraints. The surrogate models used in the approximate optimization were the response surface model, Kriging model, and radial basis function-based neural network. The approximate optimization results were compared with the actual analysis results in terms of approximate accuracy. The radial basis function-based neural network showed the most accurate optimum design results for the fire resistance design of the A60 class deck penetration piece.

A Comparative Study on Approximate Models and Sensitivity Analysis of Active Type DSF for Offshore Plant Float-over Installation Using Orthogonal Array Experiment (직교배열실험을 이용한 해양플랜트 플로트오버 설치 작업용 능동형 DSF의 민감도해석과 근사모델 비교연구)

  • Kim, Hun-Gwan;Song, Chang Yong
    • Journal of the Korea Convergence Society
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    • v.12 no.3
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    • pp.187-196
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    • 2021
  • The paper deals with comparative study for characteristics of approximation of design space according to various approximate models and sensitivity analysis using orthogonal array experiments in structure design of active type DSF which was developed for float-over installation of offshore plant. This study aims to propose the orthogonal array experiments based design methodology which is able to efficiently explore an optimum design case and to generate the accurate approximate model. Thickness sizes of main structure member were applied to the design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experiment. Best design case was also identified to improve the structure design with weight minimization. From the orthogonal array experiment results, various approximate models such as response surface model, Kriging model, Chebyshev orthogonal polynomial model, and radial basis function based neural network model were generated. The experiment results from orthogonal array method were validated by the approximate modeling results. It was found that the radial basis function based neural network model among the approximate models was able to approximate the design space of the active type DSF with the highest accuracy.

AN APPROXIMATE SOLUTION OF AN INTEGRAL EQUATION BY WAVELETS

  • SHIM HONG TAE;PARK CHIN HONG
    • Journal of applied mathematics & informatics
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    • v.17 no.1_2_3
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    • pp.709-717
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    • 2005
  • Integral equations occur naturally in many fields of mechanics and mathematical physics. We consider the Fredholm integral equation of the first kind.In this paper we are interested in integral equation of convolution type. We give approximate solution by Meyer wavelets

APPROXIMATE CONTROLLABILITY FOR QUASI-AUTONOMOUS DIFFERENTIAL EQUATIONS

  • JEONG JIN MUN
    • Journal of applied mathematics & informatics
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    • v.17 no.1_2_3
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    • pp.623-631
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    • 2005
  • The approximate controllability for the nonlinear control system with nonlinear monotone hemicontinuous and coercive operator is studied. The existence, uniqueness and a variation of solutions of the system are also given.

APPROXIMATE CONTROLLABILITY OF DELAY VOLTERRA CONTROL SYSTEM

  • Ryu, Jong-Won;Park, Jong-Yeoul;Kwun, Young-Chel
    • Bulletin of the Korean Mathematical Society
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    • v.30 no.2
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    • pp.277-284
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    • 1993
  • The purpose of this paper is to prove the approximate controllability results for the delay Volterra system in the case of trajectories. In method, our paper differs from [5].

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