• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.113-114
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• 2006

Vibration of a non-linear system under random excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the square mean of error was minimized was used. An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1379-1382
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• 1997

We introduce a fast implementation of the adaptive transversal filter which uses least-mean-square(LMS) algorithm. The fast Hadamard transform(FHT) is used for the implementation of the filter. By using the proposed filter we can get the significant time reduction in computatioin over the conventional time domain LMS filter at the cost of a little performance. By computer simulation, we show the comparison of the propsed Hadamard-domain filter and the time domain filter in the view of multiplication time, mean-square error and robustness for noise.

• 시스템엔지니어링학술지
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• 제16권1호
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• pp.58-67
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• 2020

A big data processing method to predict solar power generation using systems engineering approach is developed in this work. For developing analytical method, linear model (LM), support vector machine (SVN), and artificial neural network (ANN) technique are chosen. As evaluation indices, the cross-correlation and the mean square root of prediction error (RMSEP) are used. From multi-variable comparison test, it was found that ANN methodology provides the highest correlation and the lowest RMSEP.

• 대한산업공학회지
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• 제39권5호
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• pp.367-373
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• 2013

In this article, we deal with a design problem for determining the levels of noise factors in the Taguchi method. First, the proposed levels by Taguchi method is reviewed in case of smaller-the-better performance characteristics. We obtain the optimal levels of noise factors minimizing the mean square error of SN(signal to Noise) ratio and compare the optimal levels with the levels proposed by Taguchi method under the first and second order models. Secondly, the concept of V-optimality is applied to determining the levels of noise factors.

• 품질경영학회지
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• 제38권3호
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• pp.408-412
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• 2010

In this note, we deal with a design problem for determining the levels of noise factors in the Taguchi method. Recently, Ree(2009) proposed a new method to determine the levels of noise factors that is dependent on the distribution of the noise factors. We discuss the original suggestion from Taguchi method, propose a way to compare the two methods and investigate the performance(mean square error) of two proposals by examples.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1151-1160
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• 2014

In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

• 한국농공학회지
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• 제43권2호
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• pp.78-84
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• 2001

The daily streamflow in the Yaluhe watershed located in the north-eastern part of China was simulated by DAWAST model and the water balance parameters of the model were calibrated by simplex method. Model verification tests were carried out. The range of root mean square error was 0.34∼1.50mm, that of percent error in volume was -16.9∼-62.0% and that of correlation coefficient was 0.727∼0.920. DAWAST model was revised to consider the phreatic evaporation from the ground water in the frozen soil by adjusting soil moisture content in the unsaturated layer at the end of the melting season. The results of estimation of the daily streamflow by the revised model were statistically improved, that is, the range of root mean square error was 0.31∼1.49mm, that of percent error in volume was -11.7∼-12.1%, and that of correlation coefficient was 0.810∼0.932. The accuracy of DAWAST model was improved and the applicability of DAWAST model was expanded to the frozen region.

• 한국통신학회논문지
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• 제25권5B호
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• pp.830-841
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• 2000

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at iteration a upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RL algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the (B+1)times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• 한국통신학회논문지
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• 제31권3A호
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• pp.232-239
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• 2006

본 논문에서는 Wireless PAN(WPAN)을 위하여 IEEE 802.15.3a의 표준안으로 제안된 Ultra WideBand(UWB) Multi-Band OFDM(MB-OFDM) 시스템에서의 프리앰블 모델을 분석하교, 효율적이며 향상된 성능을 제공하는 심볼 타이밍 및 반송파 주파수 오프셋 추정 알고리즘을 적용한 후 AWGN 및 UWB 채널 환경에서 모의 실험을 통하여 심볼 타이밍 오프셋 추정 성능은 Detection Probability, False Alarm Probability, Missing Probability 및 Mean Acquisition Time으로, 반송파 주파수 오프셋 추정 성능은 MSE(Mean Square Error)로 확인한다.

• 대한전기학회논문지
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• 제36권8호
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• pp.584-593
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• 1987

A new combined approximation method using Routh stability array and mean-square error (MSE) method is proposed for deriving reduced-order z-transter functions for discrete time systems. The Routh stability array is used to obtain the reduced-order denominator polynomial, and the numerator polynomial is obtained by minimizing the mean-square error between the unit step responses of the original system and reduced model. The advantages of the new combined approximation method are that the reduced model is always stable provided the original model is stable and the initial and steady-state characteristics of the original model can be preserved in the reduced model.