• Title/Summary/Keyword: Non-linear Function

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Characteristics of Iλ-optimality Criterion compared to the D- and Heteroscedastic G-optimality with respect to Simple Linear and Quadratic Regression (단순선형회귀와 이차형식회귀모형을 중심으로 D-와 이분산 G-최적에 비교한 Iλ-최적실험기준의 특성연구)

  • Kim, Yeong-Il
    • Journal of Korean Society for Quality Management
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    • v.21 no.2
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    • pp.140-155
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    • 1993
  • The characteristics of $I_{\lambda}$-optimality, one of the linear criteria suggested by Fedorov (1972) are investigated with respect to the D-and heteroscedastic G-optimality in case of non-constant variance function. Though having limited results obtained from simple models, we may conclude that $I_{\lambda}$-optimality is sometimes preferred to the heteroscedastic G-optimality suggested newly bv Wong and Cook (1992) in the sense that the experimenter's belief in weighting function exists in $I_{\lambda}$-optimality criterion, not to mention its computational simplicity.

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Quasiconcave Bilevel Programming Problem

  • Arora S.R.;Gaur Anuradha
    • Management Science and Financial Engineering
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    • v.12 no.1
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    • pp.113-125
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    • 2006
  • Bilevel programming problem is a two-stage optimization problem where the constraint region of the first level problem is implicitly determined by another optimization problem. In this paper we consider the bilevel quadratic/linear fractional programming problem in which the objective function of the first level is quasiconcave, the objective function of the second level is linear fractional and the feasible region is a convex polyhedron. Considering the relationship between feasible solutions to the problem and bases of the coefficient submatrix associated to variables of the second level, an enumerative algorithm is proposed which finds a global optimum to the problem.

Design of Genetic Algorithms-based Fuzzy Polynomial Neural Networks Using Symbolic Encoding (기호 코딩을 이용한 유전자 알고리즘 기반 퍼지 다항식 뉴럴네트워크의 설계)

  • Lee, In-Tae;Oh, Sung-Kwun;Choi, Jeoung-Nae
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.270-272
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    • 2006
  • In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

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Reliability analysis by numerical quadrature and maximum entropy method

  • Zhu, Tulong
    • Structural Engineering and Mechanics
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    • v.3 no.2
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    • pp.135-144
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    • 1995
  • Since structural systems may fail in any one of several failure modes, computation of system reliability is always difficult. A method using numerical quadrature for computing structural system reliability with either one or more than one failure mode is presented in this paper. Statistically correlated safety margin equations are transformed into a group of uncorrelated variables and the joint density function of these uncorrelated variables can be generated by using the Maximum Entropy Method. Structural system reliability is then obtained by integrating the joint density function with the transformed safety domain enclosed within a set of linear equations. The Gaussian numerical integration method is introduced in order to improve computational accuracy. This method can be used to evaluate structural system reliability for Gaussian or non-Gaussian variables with either linear or nonlinear safety boundaries. It is also valid for implicit safety margins such as computer programs. Both the theory and the examples show that this method is simple in concept and easy to implement.

Nonlinear responses of an arbitrary FGP circular plate resting on the Winkler-Pasternak foundation

  • Arefi, Mohammad;Allam, M.N.M.
    • Smart Structures and Systems
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    • v.16 no.1
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    • pp.81-100
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    • 2015
  • This paper presents nonlinear analysis of an arbitrary functionally graded circular plate integrated with two functionally graded piezoelectric layers resting on the Winkler-Pasternak foundation. Geometric nonlinearity is considered in the strain-displacement relation based on the Von-Karman assumption. All the mechanical and electrical properties except Poisson's ratio can vary continuously along the thickness of the plate based on a power function. Electric potential is assumed as a quadratic function along the thickness direction. After derivation of general nonlinear equations, as an instance, numerical results of a functionally graded material integrated with functionally graded piezoelectric material obeying two different functionalities is investigated. The effect of different parameters such as parameters of foundation, non homogenous index and boundary conditions can be investigated on the mechanical and electrical results of the system. A comprehensive comparison between linear and nonlinear responses of the system presents necessity of this study. Furthermore, the obtained results can be validated by using previous linear and nonlinear analyses after removing the effect of foundation.

Construction and verification of nonparameterized ship motion model based on deep neural network

  • Wang Zongkai;Im Nam-kyun
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.170-171
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    • 2022
  • A ship's maneuvering motion model is important in a computer simulation, especially under the trend of intelligent navigation. This model is usually constructed by the hydrodynamic parameters of the ship which are generated by the principles of hydrodynamics. Ship's motion model is a nonlinear function. By using this function, ships' motion elements can be calculated, then the ship's trajectory can be predicted. Deeping neural networks can construct any linear or non-linear equation theoretically if there have enough and sufficient training data. This study constructs some kinds of deep Networks and trains this network by real ship motion data, and chooses the best one of the networks, uses real data to train it, then uses it to predict the ship's trajectory, getting some conclusions and experiences.

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Experimental Study on Equivalent Linear System for Rotational friction Damper (회전마찰감쇠기의 등가선형시스템에 관한 실험적 연구)

  • 김형섭;박지훈;민경원;이상현;이명규
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.10a
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    • pp.296-303
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    • 2004
  • In this study, equivalent linear damping and stiffness of a single-degree-of-freedom (SDOF) structure with a rotational friction damper are estimated using the result of experiments and compared with those obtained from non-linear time history analyses. First, the transfer function of the test model is constructed and then the equivalent stiffness and damping are calculated, using the half-power bandwidth (HPB) method. For comparative study, those properties are estimated based on stochastic theory in the time domain. Both equivalent linear systems identified from experiments and numerical analyses correspond well. Further, it is observed that there exists an optimal clamping force on the rotational friction damper from estimated equivalent damping.

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Mathematical Programming Models for Establishing Dominance with Hierarchically Structured Attribute Tree (계층구조의 속성을 가지는 의사결정 문제의 선호순위도출을 위한 수리계획모형)

  • Han, Chang-Hee
    • Journal of the military operations research society of Korea
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    • v.28 no.2
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    • pp.34-55
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    • 2002
  • This paper deals with the multiple attribute decision making problem when a decision maker incompletely articulates his/her preferences about the attribute weight and alternative value. Furthermore, we consider the attribute tree which is structured hierarchically. Techniques for establishing dominance with linear partial information are proposed in a hierarchically structured attribute tree. The linear additive value function under certainty is used in the model. The incompletely specified information constructs a feasible region of linear constraints and therefore the pairwise dominance relationship between alternatives leads to intractable non-linear programming. Hence, we propose solution techniques to handle this difficulty. Also, to handle the tree structure, we break down the attribute tree into sub-trees. Due to there cursive structure of the solution technique, the optimization results from sub-trees can be utilized in computing the value interval on the topmost attribute. The value intervals computed by the proposed solution techniques can be used to establishing the pairwise dominance relation between alternatives. In this paper, pairwise dominance relation will be represented as strict dominance and weak dominance, which ware already defined in earlier researches.

NNDI decentralized evolved intelligent stabilization of large-scale systems

  • Chen, Z.Y.;Wang, Ruei-Yuan;Jiang, Rong;Chen, Timothy
    • Smart Structures and Systems
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    • v.30 no.1
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    • pp.1-15
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    • 2022
  • This article focuses on stability analysis and fuzzy controller synthesis for large neural network (NN) systems consisting of several interconnected subsystems represented by the NN model. Advanced and fuzzy NN differential inclusion (NNDI) for stability based on the developed algorithm with H infinity can be designed based on the evolved biological design. This representation is constructed using sector linearity for NN models. Sector linearity transforms a non-linear model into a linear model based on proposed operations. New sufficient conditions are realized in the form of LMI (linear matrix inequalities) to ensure the asymptotic stability of the trans-Lyapunov function. This transforms the nonlinear model into a linear model based on multiple rules. At last, a numerical case study with simulations is derived as illustration to prove its feasibility in real nonlinear structures.

NUMERICAL SIMULATION OF DAM-BROKEN PROBLEMS USING A PARTICLE METHOD (입자법을 이용한 댐 붕괴의 수치 시뮬레이션)

  • Lee, B.H.;Jung, S.J.;Kim, Y.H.;Park, J.C.
    • Journal of computational fluids engineering
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    • v.13 no.1
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    • pp.28-34
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    • 2008
  • A particle method recognized as one of the gridless methods has been developed to investigate the nonlinear free-surface motions interacting to the structures. The method is more feasible and effective than convectional grid methods for solving the non-linear free-surface motion with complicated boundary shapes. The right-handed side of the governing equations for incompressible fluid, which includes gradient, viscous and external force terms, can be replaced by the particle interaction models. In the present study, the developed method is applied to the dam-broken problem on dried- and wet-floor and its adequacy will be discussed by the comparison with the experimental results.