• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.633-641
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• 2001

The least squares method is usually applied when estimating the parameters in the regression models. However the least square estimator is not very efficient when the distribution of the error is skewed. In this paper, we propose the asymmetric least square estimator for a particular nonlinear time series regression model, and give the simple and practical sufficient conditions for the strong consistency of the estimators.

• Journal of the military operations research society of Korea
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• v.13 no.1
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• pp.91-100
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• 1987

This paper deals with an algorithm for solving nonlinear programming problems with equality constraints. Nonlinear programming problems are transformed into a square sums of nonlinear functions by the Lagrangian multiplier method. And an iteration method minimizing this square sums is suggested and then an algorithm is proposed. Also theoretical basis of the algorithm is presented.

• Journal of Ocean Engineering and Technology
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• v.22 no.3
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• pp.41-46
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• 2008

It is a recent trend for advanced ships and submarines to incorporate composite structures with viscoelastically damping material. Much research has been done on curve-fitting techniquesto identify vibration characteristic parameters such as natural frequencies, modal damping ratios, and mode shapes of the composite structure. In this study, an advanced technique for accurately determining vibration characteristic of a circular cylindrical shell-attached viscoelastically damping material is used, based on a multi-degree of freedom (MDOF) curve-fitting method. First, an initial value is obtained by using a linear least square method. Next, using the initial value, the exact modal parameters of the composite circular cylindrical shell are obtained by using a nonlinear least square method. Results show computation time is greatly decreased and accurate results are obtained by the MDOF curve-fitting method.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.

• International Journal of Highway Engineering
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• v.18 no.4
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• pp.63-68
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• 2016

PURPOSES : The nonlinear model of fatigue cracking is typically used for determining the maintenance period. However, this requires that the model parameters be known. In this study, the particle filter (PF) method was used to determine various statistical parameters such as the mean and standard deviation values for the nonlinear model of fatigue cracking. METHODS : The PF method was used to determine various statistical parameters for the nonlinear model of fatigue cracking, such as the mean and standard deviation. RESULTS : On comparing the values obtained using the PF method and the least square (LS) method, it was found that PF method was suitable for determining the statistical parameters to be used in the nonlinear model of fatigue cracking. CONCLUSIONS : The values obtained using the PF method were as accurate as those obtained using the LS method. Furthermore, reliability design can be applied because the statistical parameters of mean and standard deviation can be obtained through the PF method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.873-876
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• 2005

The nonlinear characteristics of a damper is directly related to the car behavior and performance, both for handling and comfort. So considering the nonlinear characteristics of a damper such as hysteresis is important to analyze the dynamic characteristics of a car suspension. In this study, a mathematical nonlinear dynamic damper model based on experimental data is devised to estimate the nonlinear parameters of a NEW EF-SONATA damper using the least square method. The devised nonlinear dynamic damper model is used to analyze the reaction force of a NEW EF-SONATA suspension using ADAMS. The simulation results are good agreement with the experimental data than those of the linear model.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.537-539
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• 1998

In this paper, we construct the on-line model structure for the nonlinear process systems using the adaptive fuzzy-neural network. Adaptive fuzzy-neural network usually consists of two distinct modifiable structure, with both, the premise and the consequent part. These two parts can be adapted by different optimization methods, which are the hybrid learning procedure combining gradient descent method and least square method. To achieve the on-line model structure, we use the recursive least square method for the consequent parameter identification of nonlinear process. We design the interface between PLC and main computer, and construct the monitoring and control simulator for the nonlinear process. The proposed on-line modeling to real process is carried out to obtain the effective and accurate results.

• Journal of Korean Port Research
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• v.15 no.1
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• pp.87-97
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• 2001

The calculation of earthwork plays a major role in plan or design of many civil engineering projects, and thus it has become very important to advanced the accuracy of earthwork calculation. Current method used for estimating the volume of pit excavation assumes that the ground profile between the grid points is linear(trapezoidal rule), or nonlinear(simpson's formulas). In this paper the spot height method, least square method, and chamber formulas, Chen and Lin method are compared with the volumes of the pits in these examples. As a result of this study, algorithm of chen and Lin me쇙 by spline method should provide a better accuracy than the spot height method, least square method, chamber formulas. The Chen and Lin formulas can be used for estimating the excavation volume of a pit divide into a grid with unequal intervals. From the characteristics of the cubic spline polynomial, the modeling curve of the Chen and Lin method is smooth and matches the ground profile well. Generally speaking, the nonlinear profile formulas provide better accuracy than the linear profile formulas. The mathematical model mentioned make an offer maximum accuracy in estimating the volume of a pit excavation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.366-366
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• 2000

In this paper, an adaptive neuro-fuzzy filter using the conditional fuzzy c-means(CFCM) methods is proposed. Usualy, the number of fuzzy rules exponentially increases by applying the grid partitioning of the input space, in conventional adaptive neuro-fuzzy inference system(ANFIS) approaches. In order to solve this problem, CFCM method is adopted to render the clusters which represent the given input and output data. Parameter identification is performed by hybrid learning using back-propagation algorithm and total least square(TLS) method. Finally, we applied the proposed method to the nonlinear channel equalization problem and obtained a better performance than previous works.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.205-209
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• 2013

A conventional acoustic echo suppressor (AES) considering only room impulse response between a loudspeaker and a microphone eliminates acoustic echo from the microphone input. However, in a nonlinear acoustic echo environment, the conventional AES degraded because of a nonlinearity of the loudspeaker. In this paper, we adopt AES based on the frequency-domain second-order Volterra filter using Least Square method. For comparing performances, we conduct objective tests including Echo Return Loss Enhancement (ERLE) and Speech Attenuation (SA). The proposed algorithm shows better performance than the conventional in both linear and nonlinear acoustic echo environments.