• Title/Summary/Keyword: Estimation factor

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Wind-induced dynamic response and its load estimation for structural frames of circular flat roofs with long spans

  • Uematsu, Yasushi;Yamada, Motohiko
    • Wind and Structures
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    • v.5 no.1
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    • pp.49-60
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    • 2002
  • This paper describes a simple method for evaluating the design wind loads for the structural frames of circular flat roofs with long spans. The dynamic response of several roof models were numerically analyzed in the time domain as well as in the frequency domain by using wind pressure data obtained from a wind tunnel experiment. The instantaneous displacement and bending moment of the roof were computed, and the maximum load effects were evaluated. The results indicate that the wind-induced oscillation of the roof is generally dominated by the first mode and the gust effect factor approach can be applied to the evaluation of the maximum load effects. That is, the design wind load can be represented by the time-averaged wind pressure multiplied by the gust effect factor for the first mode. Based on the experimental results for the first modal force, an empirical formula for the gust effect factor is provided as a function of the geometric and structural parameters of the roof and the turbulence intensity of the approach flow. The equivalent design pressure coefficients, which reproduce the maximum load effects, are also discussed. A simplified model of the pressure coefficient distribution is presented.

A New Statistical Approach for the Estimation of Range and Degree of Fisheries Damages Caused by Public Undertaking (공공사업으로 인한 어업피해 범위와 피해정도 추정의 새로운 통계학적 접근)

  • 강용주;김기수;장창익;박청길;이종섭
    • The Journal of Fisheries Business Administration
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    • v.35 no.1
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    • pp.117-132
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    • 2004
  • This study attempts to suggest a new approach of the estimation of range and degree of fisheries damages caused by a large scale of reclamation undertaken in coastal area using the central limit theorem(CLT) in statistics. The key result of the study is the introduction of the new concept of critical variation of environmental factor($d_{c}$). The study defines $d_{c}$ as a standard deviation of the sample mean($\bar{X}$) of environmental factor(X), in other words, $\frac{\sigma}{ \sqrt{n}}$. The inner bound of $d_{c}$ could be the area of fisheries damages caused by public coastal undertaking. The study also defines the decreasing rate of fisheries production$\delta_{\varepsilon}$, in other words, degree of fisheries damages, as the rate of change in the distribution of sample mean(($\bar{X}$), caused by the continuous and constant variation of environmental factor. Therefore $\delta_{\varepsilon}$ can be easily calculated by the use of table of the standardized normal distribution.

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Directional Design Hourly Volume Estimation Model for National Highways (일반국도의 중방향 설계시간 교통량 추정 모형)

  • Lim, Sung-Han;Ryu, Seung-Ki;Byun, Sang-Cheol;Moon, Hak-Yong
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.3
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    • pp.13-22
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    • 2012
  • Estimating directional design hourly volume (DDHV) is an important aspect of traffic or road engineering practice. DDHV on highway without permanent traffic counters (PTCs) is usually determined by the annual average daily traffic (AADT) being multiplied by the ratio of DHV to AADT (K factor) and the directional split ratio (D factor) recommended by Korea highway capacity manual (KHCM). However, about the validity of this method has not been clearly proven. The main intent of this study is to develop more accurate and efficient DDHV estimation models for national highway in Korea. DDHV characteristics are investigated using the data from permanent traffic counters (PTCs) on national highways in Korea. A linear relationship between DDHV and AADT was identified. So DDHV estimation models using AADT were developed. The results show that the proposed models outperform the KHCM method with the mean absolute percentage errors (MAPE).

Quantitative Comparison of Activity Calculation Methods for the Selection of Most Reliable Radionuclide Inventory Estimation

  • Hwang, Ki-Ha;Lee, Sang-Chul;Lee, Kun-Jai;Jeong, Chan-Woo;Ahn, Sang-Myeon;Kim, Tae-Wook;Kim, Kyoung-Doek;Herr, Y.H.
    • Proceedings of the Korean Radioactive Waste Society Conference
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    • 2003.11a
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    • pp.322-327
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    • 2003
  • It is important to know the accurate radionuclide inventory of radioactive waste for the reliable management. However, estimation of radionuclide concentrations in drummed radioactive waste is difficult and unreliable because of difficulties of direct detection, high cost, and radiation exposure of sampling personnel. In order to overcome these difficulties, scaling factors (SFs) have been used to assess the activities of radionuclides that could not be directly analyzed. A radionuclide assay system has been operated at KORI site since 1996 and consolidated scaling factor method has played a dominant role in determination of radionuclides concentrations. However, some problems are still remained such as uncertainty of estimated scaling factor values, inaccuracy of analyzed sample values, and disparity between the actual and ideal correlation pairs and the others. Therefore, it needs to improve the accuracy of scaling factor values. The scope of this paper is focused on the improvement of accuracy and representativeness of calculated scaling factor values based on statistical techniques. For the selection of reliable activity determination method, the accuracy of estimated SF values for each activity determination method is compared. From the comparison of each activity determination methods, it is recommended that SF determination method should be changed from the arithmetic mean to the geometrical mean for more reliable estimation of radionuclide activity. Arithmetic mean method and geometric mean method are compared based on the data set in KORI system.

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Evolutionary Algorithms with Distribution Estimation by Variational Bayesian Mixtures of Factor Analyzers (변분 베이지안 혼합 인자 분석에 의한 분포 추정을 이용하는 진화 알고리즘)

  • Cho Dong-Yeon;Zhang Byoung-Tak
    • Journal of KIISE:Software and Applications
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    • v.32 no.11
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    • pp.1071-1083
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    • 2005
  • By estimating probability distributions of the good solutions in the current population, some researchers try to find the optimal solution more efficiently. Particularly, finite mixtures of distributions have a very useful role in dealing with complex problems. However, it is difficult to choose the number of components in the mixture models and merge superior partial solutions represented by each component. In this paper, we propose a new continuous evolutionary optimization algorithm with distribution estimation by variational Bayesian mixtures of factor analyzers. This technique can estimate the number of mixtures automatically and combine good sub-solutions by sampling new individuals with the latent variables. In a comparison with two probabilistic model-based evolutionary algorithms, the proposed scheme achieves superior performance on the traditional benchmark function optimization. We also successfully estimate the parameters of S-system for the dynamic modeling of biochemical networks.

The Control of Single Phase Power Factor PWM converter using Reduced-Order Luenberger Observer (축소차원 Luenberger 관측기를 이용한 단산 PWM 컨버터의 고역률 제어)

  • 양이우;이용근;김영석
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.485-488
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    • 1999
  • In this paper, a current control system for single phase PWM AC/DC converter without the source voltage sensors is proposed. The sinusoidal input current and unity effective power factor are realised based on the estimated source voltage in the controller. The estimation of source voltage is performed by the reduced-order Luenberger observer using actual currents. The estimated source voltage is used to accomplish unity power factor. The proposed method is proved by experiments.

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A Study on Reduced Variance Self-Tuning Algorithm Using a Variable Forgetting Factor (시변 망각 인자를 사용하는 최소 자승 추정의 극점 -배치 자기동조 알고리즘에 관한 연구)

  • Park, Chan-Young;Do, Mi-Sun;Park, Mi-Gnon;Lee, Sang-Bae
    • Proceedings of the KIEE Conference
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    • 1988.07a
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    • pp.305-308
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    • 1988
  • Pole assignment controller with variable forgetting factor is generalizaed to allow the output and/or input variance to be reduced. The algorithm can give significant reductions in variance for little extra computational effort and is presented for servo-tracking using leat-squares estimation. Moreover, the use of a variable forgetting factor with correct choice of information bound can avoid 'blowing-up' of the covariance matrix of the estimates and subsequent unstable control.

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Design of Lateral Force Estimation Model for Rough Terrain Mobile Robot and Improving Estimation Reliability on Friction Coefficient (야지 주행 로봇을 위한 횡 방향 힘 추정 모델의 설계 및 마찰계수 추정 신뢰도의 향상)

  • Kim, Jiyong;Lee, Jihong;Joo, Sang Hyun
    • The Journal of Korea Robotics Society
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    • v.13 no.3
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    • pp.174-181
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    • 2018
  • For a mobile robot that travels along a terrain consisting of various geology, information on tire force and friction coefficient between ground and wheel is an important factor. In order to estimate the lateral force between ground and wheel, a lot of information about the model and the surrounding environment of the vehicle is required in conventional method. Therefore, in this paper, we are going to estimate lateral force through simple model (Minimal Argument Lateral Slip Curve, MALSC) using only minimum data with high estimation accuracy and to improve estimation reliability of the friction coefficient by using the estimated lateral force data. Simulation is carried out to analyze the correlation between the longitudinal and transverse friction coefficients and slip angles to design the simplified lateral force estimation model by analysing simulation data and to apply it to the actual field environment. In order to verify the validity of the equation, estimation results are compared with the conventional method through simulation. Also, the results of the lateral force and friction coefficient estimation are compared from both the conventional method and the proposed model through the actual robot running experiments.

Analyzing errors in selectivity estimation using the multilevel grid file (계층 그리드 화일을 이용한 선택률 추정에서 발생되는 오차 분석)

  • 김상욱;황환규;황규영
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.9
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    • pp.24-36
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    • 1996
  • In this paper, we discuss the errors in selectivity estimation using the multilevel grid file (MLGF). We first demonstrate that the estimatio errors stem from the uniformity assumption that records are uniformly distributed in their belonging region represented by an entry in a level of an MLGF directory. Bsed on this demonstration, we then investigate five factors affecting the accuracy of estimation: (1) the data distribution in a region (2) the number of records stored in an MLFG (3) the page size, (4) the query region size, and (5) the level of an MLFG directory. Next we present the tendancy of estimation errors according to the change of values for each factor through experiments. The results show that the errors decrease when (1) the distribution of records in a region becomes closer to the uniform one, (2) the number of records in an MLFG increases, (3) the page size decreases, (4) the query region size increases, and (5) the level of an MLFG directory employed as data distribution information becomes lower. After the definition of the granule ratio, the core formula representing the basic relationship between the estimation errors and the above five factors, we finally examine the change of estimation errors according to the change of the values for the granule ratio through experiments. The results indicate that errors tend to be similar depending on the values for the granule ratio regardless of the various changes of the values for the five factors. factors affecting the accuracy of estimation:

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Noise-Robust Speech Recognition Using Histogram-Based Over-estimation Technique (히스토그램 기반의 과추정 방식을 이용한 잡음에 강인한 음성인식)

  • 권영욱;김형순
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.6
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    • pp.53-61
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    • 2000
  • In the speech recognition under the noisy environments, reducing the mismatch introduced between training and testing environments is an important issue. Spectral subtraction is widely used technique because of its simplicity and relatively good performance in noisy environments. In this paper, we introduce histogram method as a reliable noise estimation approach for spectral subtraction. This method has advantages over the conventional noise estimation methods in that it does not need to detect non-speech intervals and it can estimate the noise spectra even in time-varying noise environments. Even though spectral subtraction is performed using a reliable average noise spectrum by the histogram method, considerable amount of residual noise remains due to the variations of instantaneous noise spectrum about mean. To overcome this limitation, we propose a new over-estimation technique based on distribution characteristics of histogram used for noise estimation. Since the proposed technique decides the degree of over-estimation adaptively according to the measured noise distribution, it has advantages to be few the influence of the SNR variation on the noise levels. According to speaker-independent isolated word recognition experiments in car noise environment under various SNR conditions, the proposed histogram-based over-estimation technique outperforms the conventional over-estimation technique.

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