• Title/Summary/Keyword: Constrained linear model

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SPLINE HAZARD RATE ESTIMATION USING CENSORED DATA

  • Na, Myung Hwan
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.3 no.2
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    • pp.99-106
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    • 1999
  • In this paper, the spline hazard rate model to the randomly censored data is introduced. The unknown hazard rate function is expressed as a linear combination of B-splines which is constrained to be linear(or constant) in tails. We determine the coefficients of the linear combination by maximizing the likelihood function. The number of knots are determined by Bayesian Information Criterion. Examples using simulated data are used to illustrate the performance of this method under presenting the random censoring.

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Vibration Characteristic Study of Arc Type Shell Using Active Constrained Layer Damping (능동 구속감쇠층을 이용한 아크형태 셸 모델에 대한 진동특성 연구)

  • 고성현;박현철;황운봉;박철휴
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.14 no.3
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    • pp.193-200
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    • 2004
  • The Active Constrained Layer Damping(ACLD) combines the simplicity and reliability of passive damping with the low weight and high efficiency of active control to attain high damping characteristics. The proposed ACLD treatment consists of a viscoelastic damping which is sandwiched between an active piezoelectric layer and a host structure. In this manner, the smart ACLD consists of a Passive Constrained Layer Damping(PCLD) which is augmented with an active control in response to the structural vibrations. The arc type shell model is introduced to describe the interactions between the vibrating host structure, piezoelectric actuator and viscoelastic damping. The system is modeled by applying ARMAX model and changing a state-space form through the system identification method. An optimum control law for the piezo actuator is obtain by LQR(Linear Quadratic Regulator) method. The performance of the ACLD system is determined and compared with PCLD in order to demonstrate the effectiveness of the ACLD treatment. Also, the actuation capability of a piezo actuator is examined experimentally by varying thickness of viscoelastic material(VEM).

Flood damage cost projection in Korea using 26 GCM outputs (26 GCM 결과를 이용한 미래 홍수피해액 예측)

  • Kim, Myojeong;Kim, Gwangseob
    • Journal of Korea Water Resources Association
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    • v.51 no.spc
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    • pp.1149-1159
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    • 2018
  • This study aims to predict the future flood damage cost of 113 middle range watersheds using 26 GCM outputs, hourly maximum rainfall, 10-min maximum rainfall, number of days of 80 mm/day, daily rainfall maximum, annual rainfall amount, DEM, urbanization ratio, population density, asset density, road improvement ratio, river improvement ratio, drainage system improvement ratio, pumping capacity, detention basin capacity and previous flood damage costs. A constrained multiple linear regression model was used to construct the relationships between the flood damage cost and other variables. Future flood damage costs were estimated for different RCP scenarios such as 4.5 and 8.5. Results demonstrated that rainfall related factors such as annual rainfall amount, rainfall extremes etc. widely increase. It causes nationwide future flood damage cost increase. Especially the flood damage cost for Eastern part watersheds of Kangwondo and Namgang dam area may mainly increase.

A Multi-period Behavioral Model for Portfolio Selection Problem

  • Pederzoli, G.;Srinivasan, R.
    • Journal of the Korean Operations Research and Management Science Society
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    • v.6 no.2
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    • pp.35-49
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    • 1981
  • This paper is concerned with developing a Multi-period Behavioral Model for the portfolio selection problem. The unique feature of the model is that it treats a number of factors and decision variables considered germane in decision making on an interrelated basis. The formulated problem has the structure of a Chance Constrained programming Model. Then empoloying arguments of Central Limit Theorem and normality assumption the stochastic model is reduced to that of a Non-Linear Programming Model. Finally, a number of interesting properties for the reduced model are established.

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Robust Predictive Control of Uncertain Nonlinear System With Constrained Input

  • Son, Won-Kee;Park, Jin-Young;Kwon, Oh-Kyu
    • Transactions on Control, Automation and Systems Engineering
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    • v.4 no.4
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    • pp.289-295
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    • 2002
  • In this paper, a linear matrix inequality(LMI)-based robust control method, which combines model predictive control(MPC) with the feedback linearization(FL), is presented for constrained nonlinear systems with parameter uncertainty. The design procedures consist of the following 3 steps: Polytopic description of nonlinear system with a parameter uncertainty via FL, Mapping of actual input constraint by FL into constraint on new input of linearized system, Optimization of the constrained MPC problem based on LMI. To verify the performance and usefulness of the control method proposed in this paper, some simulations with application to a flexible single link manipulator are performed.

Optimization of Model based on Relu Activation Function in MLP Neural Network Model

  • Ye Rim Youn;Jinkeun Hong
    • International journal of advanced smart convergence
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    • v.13 no.2
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    • pp.80-87
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    • 2024
  • This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.

Analysis of Dynamic Production Planning Model Using Linear Programming (선형계획을 이용한 동적 생산계획 모형의 분석)

  • Chang, Suk-Hwa
    • Journal of Korean Institute of Industrial Engineers
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    • v.19 no.3
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    • pp.71-79
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    • 1993
  • Dynamic production planning problems are to determine the optimal production times and production quantities of product for discrete finite periods. In previous many researches, the solutions for these problems have been developed through the algorithms using dynamic programming. The purpose of this research is to suggest the new algorithm using linear programming. This research is to determine optimal production quantities of product in each period to satisfy dynamic for discrete finite periods, minimizing the total of production cost and inventory holding cost. Cost functions are concave, and no backlogging for product is allowed. The new algorithm for capacity constrained problem is developed.

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Optimal Var allocation in System planning by Stochastic Linear Programming(II) (확률선형 계획법에 의한 최적 Var 배분 계뵉에 관한 연구(II))

  • Song, Kil-Yeong;Lee, Hee-Yoeng
    • Proceedings of the KIEE Conference
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    • 1989.11a
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    • pp.191-193
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    • 1989
  • This paper presents a optimal Var allocation algorithm for minimizing power loss and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A stochastic Linear Programming technique based on chance constrained method is applied to solve the probabilistic constraint. The test result in IEEE-14 Bus model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before Var allocation.

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Optimal Var Allocation in system planning by stochastic Linear Programming (확률 선형 계획법에 의한 최적 Var 배분 계획에 관한 연구)

  • Song, Kil-Yeong;Lee, Hee-Yeong
    • Proceedings of the KIEE Conference
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    • 1988.07a
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    • pp.863-865
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    • 1988
  • This paper presents a optimal Var allocation algorithm for minimizing transmission line losses and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A Stocastic Linear programming technique based on chance constrained method is applied, to solve the var allocation problem with probabilistic constraint. The test result in 6-Bus Model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before var allocation.

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Analysis of the Crop Damage Area Related to Flood by Climate Change Using a Constrained Multiple Linear Regression Model (구속 다중선형회귀 모형을 이용한 기후변화에 따른 농작물 홍수 피해 면적 분석)

  • Kim, Myojeong;Kim, Gwangseob
    • Journal of The Korean Society of Agricultural Engineers
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    • v.62 no.2
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    • pp.1-15
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    • 2020
  • In this study, the characteristics of crop damage area by flooding for 113 middle range watersheds during 2000-2016 were analyzed and future crop damage area by flooding were analyzed using 13 GCM outputs such as hourly maximum rainfall, 10-min maximum rainfall, number of days of 80 mm/day, daily rainfall maximum, annual rainfall amount associated with RCP 4.5 and RCP 8.5 scenarios and watershed characteristic data such as DEM, urbanization ratio, population density, asset density, road improvement ratio, river improvement ratio, drainage system improvement ratio, pumping capacity, detention basin capacity, and crop damage area by flooding. A constrained multiple linear regression model was used to construct the relationships between the crop damage area by flooding and other variables. Future flood index related to crop damage may mainly increase in the Mankyung watershed, Southwest part of Youngsan and Sumjin river basin and Southern part of Nackdong river basin. Results are useful to identify watersheds which need to establish strategies for responding to future flood damage.