• Title/Summary/Keyword: Linear Probability Model

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A Study on Developing An Experimental Model to Solve for Optimal Forest-Level Timber Harvesting Schedules Using Linear Programming (대단지(大團地) 산림(山林)의 목재생산계획(木材生産計劃) 분석(分析)을 위한 선형계획(線型計劃) 실험전산모델에 관한 연구(硏究))

  • Chung, Joo Sang;Park, Eun Sik
    • Journal of Korean Society of Forest Science
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    • v.82 no.3
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    • pp.292-304
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    • 1993
  • This research developed a forest-level harvest scheduling model using linear programming (LP). The formulations of the LP model include timber production schemes with constraints of nondecling yield forest conversion strategies, the minimum timber supply, levels and the maximum cut acrages. The model is able to generate both Model I and Model II types of input matrix in MPS format. In this paper, use of LP in building the framework of the strategic forest planning model was justified by comparing the algorithmic characteristics of LP with those of Gentan probability and binary search approaches through literature reviews. In order to demonstrate the field applicability of the model proposed. (1) the harvest scheduling problem for about 11,000-hectare case study area (Mt. Baekun area in Southern Experimental Forest of Seoul National University) was formulated and soloed and (2) the effects of the change in task regulatory timber production constraints or. optimal harvesting schedules here investigated.

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An estimation method based on autocovariance in the simple linear regression model (단순 선형회귀 모형에서 자기공분산에 근거한 최적 추정 방법)

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.2
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    • pp.251-260
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    • 2009
  • In this study, we propose a new estimation method based on autocovariance for selecting optimal estimators of the regression coefficients in the simple linear regression model. Although this method does not seem to be intuitively attractive, these estimators are unbiased for the corresponding regression coefficients. When the exploratory variable takes the equally spaced values between 0 and 1, under mild conditions which are satisfied when errors follow an autoregressive moving average model, we show that these estimators have asymptotically the same distributions as the least squares estimators. Additionally, under the same conditions as before, we provide a self-contained proof that these estimators converge in probability to the corresponding regression coefficients.

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Experimental Study on a Dolphin-Fender Mooring System for Pontoon-Type Structure (초대형 부유식 구조물의 돌핀-펜더계류시스템에 관한 실험연구)

  • Kim, Jin-Ha;Cho, Seok-Kyu;Hong, Sa-Young;Kim, Young-Shik
    • Journal of the Society of Naval Architects of Korea
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    • v.42 no.1 s.139
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    • pp.43-49
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    • 2005
  • in this paper a dolphin-fender moored pontoon-type floating structure in shallow water depth is studied focusing on mooring force. The pontoon-type floating structure is 500m long, 300m wide. The structure has partially non-uniform drafts of 2.0m and 3.0m. The employed mooring system is a guyed frame type dolphin-fender system. The 1/125 scale model fender system is made of rubber tube to have hi-linear load deflection characteristics. A series of model tests has been conducted focusing on motion and fender force responses in regular and irregular waves at KRISO's ocean engineering basin Non-linear numerical simulation of fender reaction force has been carried out and the results are compared with those of model tests. The simulated rigid body motion and mooring forces also have been compared with the test results.

Measurement of Nonlinear Time-variant Source Characteristics of Intake and Exhaust Systems in Fluid Machines

  • Jang Seung-Ho;Ih Jeong-Guon
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.3E
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    • pp.87-89
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    • 2005
  • The acoustical sources of intake and exhaust systems in fluid machines are often characterized by the source impedance and strength using linear frequency-domain modeling. In the case of the sources which are nonlinear and time-variant, however, the source parameters were sometimes incorrectly obtained. In this paper, the source model and direct measurement technique are modified in order to evaluate the effect due to nonlinear and periodically time-varying source character as well as the linear property of the reflectivity of in-duct fluid machine source. With a priori known kinematical information of the source, the types of nonlinear time-variant terms can be presumed by a simple physical model, in which there is practically no restriction on the form of the model. The concept of source impedance can be extendable by introducing the linear frequency response function for each nonlinear or time-variant input. Extending the conventional method and adapting the reverse MISO technique, it is possible to develop a direct method that can deal with the nonlinear time-variant source parameters. The proposed direct method has a novel feature that there is no restriction on the probability or spectral natures of the excited sound pressure data. The present method is verified by the simulated measurements for simplified fluid machines. It is thought that the proposed method would be useful in predicting the insertion loss or the radiated sound level from intake or exhaust systems.

Optimum Design of a Simple Slope considering Multi Failure Mode (다중 파괴모드를 고려한 단순 사면의 최적 설계)

  • Kim, Hyun-Ki;Shin, Min-Ho;Choi, Chan-Yong
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.6
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    • pp.73-80
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    • 2010
  • Conventional slope stability analysis is focused on calculating minimum factor of safety or maximum probability of failure. To minimize inherent uncertainty of soil properties and analytical model and to reflect various analytical models and its failure shape in slope stability analysis, slope stability analysis method considering simultaneous failure probability for multi failure mode was proposed. Linear programming recently introduced in system reliability analysis was used for calculation of simultaneous failure probability. System reliability analysis for various analytical models could be executed by this method. Optimum design to determine angle of a simple slope is executed for multi failure mode using linear programming. Because of complex consideration for various failure shapes and modes, it is possible to secure advanced safety by using simultaneous failure probability.

Prediction of Future Sea Surface Temperature around the Korean Peninsular based on Statistical Downscaling (통계적 축소법을 이용한 한반도 인근해역의 미래 표층수온 추정)

  • Ham, Hee-Jung;Kim, Sang-Su;Yoon, Woo-Seok
    • Journal of Industrial Technology
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    • v.31 no.B
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    • pp.107-112
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    • 2011
  • Recently, climate change around the world due to global warming has became an important issue and damages by climate change have a bad effect on human life. Changes of Sea Surface Temperature(SST) is associated with natural disaster such as Typhoon and El Nino. So we predicted daily future SST using Statistical Downscaling Method and CGCM 3.1 A1B scenario. 9 points of around Korea peninsular were selected to predict future SST and built up a regression model using Multiple Linear Regression. CGCM 3.1 was simulated with regression model, and that comparing Probability Density Function, Box-Plot, and statistical data to evaluate suitability of regression models, it was validated that regression models were built up properly.

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Nonlinear Noise-Induced Transitions in Active Rotator Model

  • Kim, Seung-Hwan;Park, Seon-Hee;Ryu, Chang-Su
    • ETRI Journal
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    • v.20 no.2
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    • pp.214-230
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    • 1998
  • We investigate noise-induced transitions in active rotator model with a fluctuating threshold in the presence of an additive noise. The fluctuation of the threshold depends on the additive noise in a nonlinear fashion. In the white-noise limit of the fluctuation, the Fokker-Planck equation of the system reduces to that of the system with correlated linear fluctuation implying that the nonlinearity may be transformed into the correlation of linear noises. We also investigate the system with a nonlinear colored noise which depends on the additive noise as its square. The system shows a single peak, two peaks, and three peaks in its steady state probability distribution according to the noise intensities and the correlation time whose change leads to peak-creating, peak-splitting, and peak-merging transitions.

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Slope Stability Analysis Considering Multi Failure Mode (다중파괴모드를 고려한 사면안정해석)

  • Kim, Hyun-Ki;Kim, Soo-Sam
    • Journal of the Korean Society for Railway
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    • v.14 no.1
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    • pp.24-30
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    • 2011
  • Conventional slope stability analysis is focused on calculating minimum factor of safety or maximum probability of failure. To minimize inherent uncertainty of soil properties and analytical model and to reflect various analytical models and its failure shape in slope stability analysis, slope stability analysis method considering simultaneous failure probability for multi failure mode was proposed. Linear programming recently introduced in system reliability analysis was used for calculation of simultaneous failure probability. System reliability analysis for various analytical models could be executed by this method. For application analysis for embankment, the results of this method shows that system stability of embankment calculate quantitatively.

Higher Order Moments of Record Values From the Inverse Weibull Lifetime Model and Edgeworth Approximate Inference

  • Sultan, K.S.
    • International Journal of Reliability and Applications
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    • v.8 no.1
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    • pp.1-16
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    • 2007
  • In this paper, we derive exact explicit expressions for the triple and quadruple moments of the lower record values from inverse the Weibull (IW) distribution. Next, we present and calculate the coefficients of the best linear unbiased estimates of the location and scale parameters of IW distribution (BLUEs) for different choices of the shape parameter and records size. We then use the higher order moments and the calculated BLUEs to compute the mean, variance, and the coefficients of skewness and kurtosis of certain linear functions of lower record values. By using the coefficients of the skewness and kurtosis, we develop approximate confidence intervals for the location and scale parameters of the IW distribution using Edgeworth approximate values and then compare them with the corresponding intervals constructed through Monte Carlo simulations. Finally, we apply the findings of the paper to some simulated data.

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Mutual Information and Redundancy for Categorical Data

  • Hong, Chong-Sun;Kim, Beom-Jun
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.297-307
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    • 2006
  • Most methods for describing the relationship among random variables require specific probability distributions and some assumptions of random variables. The mutual information based on the entropy to measure the dependency among random variables does not need any specific assumptions. And the redundancy which is a analogous version of the mutual information was also proposed. In this paper, the redundancy and mutual information are explored to multi-dimensional categorical data. It is found that the redundancy for categorical data could be expressed as the function of the generalized likelihood ratio statistic under several kinds of independent log-linear models, so that the redundancy could also be used to analyze contingency tables. Whereas the generalized likelihood ratio statistic to test the goodness-of-fit of the log-linear models is sensitive to the sample size, the redundancy for categorical data does not depend on sample size but its cell probabilities itself.