• Title/Summary/Keyword: estimation methods

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Estimation of Loads on Tunnel Lining Based on Case Studies (사례연구를 통한 터널 하중의 예측)

  • 김학준
    • The Journal of Engineering Geology
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    • v.7 no.3
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    • pp.207-216
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    • 1997
  • Estimation of loads on tunnel lining is one of the major issues to be addressed in the design of a tunnel. The existing analytical methods do not consider important details of construction and the variation of geology along the tunnel axis. The measured loads obtained from several sanitary and subway tunnels in Edmonton, Alberta, Canada, are compared with the lining loads calculated using the existing analytical methods. However, the existing methods are determined to be not fully satisfactory for the estimation of lining loads. To account for face and heading effects occurring prior to lining installation, the stress reduction factor determined using Eisenstein and Negro's method is used coupled with an analytical solution for calculation of lining loads.

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Classification of the Environmental Noise Sources by considering the Characteristics of the Sound Quality (음질특성을 고려한 환경소음원의 분류에 대한 연구)

  • 황대선;조연;허덕재;조경숙
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.707-711
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    • 2004
  • Recently, the interests about noises have increased with the rapid development of our living environment Until now the estimation methods to sounds have used the equivalent levels. The sensitivities of human beings aren't considered in these methods. It's a situation to need new estimation methods for environmental noises. They must be analyzed by the characteristics of sounds before making the noise regulations newly. In this study, the noises were measured around our living environment And the frequency analysis, Sound Quality Metrics, the cluster analysis and so on are used to classify the environmental noises.

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Bootstrap methods for long-memory processes: a review

  • Kim, Young Min;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • v.24 no.1
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    • pp.1-13
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    • 2017
  • This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

Mathematical and Statistical Characterization of LD50 Estimation (LD50 산출방법에 있어서 수리 · 통계학적 특성)

  • Kim Se Ki;Kim Keun-Chong;Lee Byung Mu
    • Toxicological Research
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    • v.20 no.4
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    • pp.321-324
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    • 2004
  • Lethal dose 50% ($LD_{50}$) has been commonly used as a parameter for the estimation of acute toxicity not only in animal experiment, but also in human study. Several methods to estimate $LD_{50}$ had been introduced, but Spearman-Karber and Berens-Karber method have been widely used due to their relative convenience and accuracy. However, $LD_{50}$ values estimated from the two methods showed inconsistency and variation depending on the characteristics of mortality data. In this study, the two methods were comparatively investigated in terms of accuracy and stability for the estimation of $LD_{50}$.

Comprehensive studies of Grassmann manifold optimization and sequential candidate set algorithm in a principal fitted component model

  • Chaeyoung, Lee;Jae Keun, Yoo
    • Communications for Statistical Applications and Methods
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    • v.29 no.6
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    • pp.721-733
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    • 2022
  • In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

Joint Estimation of TOA and DOA in IR-UWB System Using Sparse Representation Framework

  • Wang, Fangqiu;Zhang, Xiaofei
    • ETRI Journal
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    • v.36 no.3
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    • pp.460-468
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    • 2014
  • This paper addresses the problem of joint time of arrival (TOA) and direction of arrival (DOA) estimation in impulse radio ultra-wideband systems with a two-antenna receiver and links the joint estimation of TOA and DOA to the sparse representation framework. Exploiting this link, an orthogonal matching pursuit algorithm is used for TOA estimation in the two antennas, and then the DOA parameters are estimated via the difference in the TOAs between the two antennas. The proposed algorithm can work well with a single measurement vector and can pair TOA and DOA parameters. Furthermore, it has better parameter-estimation performance than traditional propagator methods, such as, estimation of signal parameters via rotational invariance techniques algorithms matrix pencil algorithms, and other new joint-estimation schemes, with one single snapshot. The simulation results verify the usefulness of the proposed algorithm.

On-line System Identification using State Observer

  • Park, Duck-Gee;Hong, Suk-Kyo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2538-2541
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    • 2005
  • This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

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Angle-Range-Polarization Estimation for Polarization Sensitive Bistatic FDA-MIMO Radar via PARAFAC Algorithm

  • Wang, Qingzhu;Yu, Dan;Zhu, Yihai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2879-2890
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    • 2020
  • In this paper, we study the estimation of angle, range and polarization parameters of a bistatic polarization sensitive frequency diverse array multiple-input multiple-output (PSFDA-MIMO) radar system. The application of polarization sensitive array in receiver is explored. A signal model of bistatic PSFDA-MIMO radar system is established. In order to utilize the multi-dimensional structure of array signals, the matched filtering radar data can be represented by a third-order tensor model. A joint estimation of the direction-of-departure (DOD), direction-of-arrival (DOA), range and polarization parameters based on parallel factor (PARAFAC) algorithm is proposed. The proposed algorithm does not need to search spectral peaks and singular value decomposition, and can obtain automatic pairing estimation. The method was compared with the existing methods, and the results show that the performance of the method is better. Therefore, the accuracy of the parameter estimation is further improved.

Noise Estimation Using Edge Detection (에지 검출을 이용한 잡음 예측)

  • Kim, Young-Ro;Dong, Sung-Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.281-286
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    • 2013
  • In this paper, we propose a noise estimation method using edge detection. It is a filter-based noise estimation method. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use a modified rational filter which is robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of images and has better results than those of conventional filter-based noise estimation methods.

Minimum Entropy Deconvolution을 이용한 지하수 상대 재충진양의 시계열 추정법

  • 김태희;이강근
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2003.09a
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    • pp.574-578
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    • 2003
  • There are so many methods to estimate the groundwater recharge. These methods can be categorized into four groups. First groupis related to the water balance analysis, second group is concerned with baseflow/springflow recession, and third group is interested in some types of tracers; environmental tracers and/or temperature profile. The limitation of these types of methods is that the estimated results of recharge are presented in the form of an average over some time period. Forth group has a little different approach. They use the time series data of hydraulic head and specific yield evaluated from field test, and the results of estimation are described in the sequential form. But their approach has a serious problem. The estimated results in forth typeof methods are generally underestimated because they cannot consider the discharge phase of water table fluctuation coupled with the recharge phase. Ketchum el. at. (2000) proposed calibrated method, considering recharge- and discharge-coupled water table fluctuation. But the dischargeis considered just as the areal average with discharge rate. On the other hand, there are many methods to estimate the source wavelet with observed data set in geophysics/signal processing and geophysical methods are rarely applied to the estimation of groundwater recharge. The purpose this study is the evaluation of the applicability of one of the geophysical method in the estimation of sequential recharge rate. The applied geophysical method is called minimum entropy deconvolution (MED). For this purpose, numerical modeling with linearized Boussinesq equation was applied. Using the synthesized hydraulic head through the numerical modeling, the relative sequenceof recharge is calculated inversely. Estimated results are very concordant with the applied recharge sequence. Cross-correlations between applied recharge sequence and the estimated results are above 0.985 in all study cases. Through the numerical test, the availability of MED in the estimation of the recharge sequence to groundwater was investigated

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