• Title/Summary/Keyword: 데이터 추정

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Study of assuming system on moving route of the indoor self driving robot (실내형 자율 주행 로봇의 이동 경로 추정 시스템에 관한 연구)

  • Lee, Jang-Woo;Jo, Kyung-Hwa;Jung, Hee-Seung;Kim, Eung-Soo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.370-371
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    • 2015
  • 자율 주행 로봇의 기본적인 기능에는 위치 추정 기능과 무선 통신 기능이 포함된다. 이미지 센서를 이용하여 로봇의 이동 위치를 추정하고, 무선통신은 ZigBee를 적용하였다. 본 논문에서는 자율 주행 로봇의 이동 위치 정보를 이미지센서를 이용하여 데이터를 취득 후 마우스 알고리즘을 통해 이동 데이터로 환산하였으며, 이동 데이터를 ZigBee통신을 통해 서버와 실시간 통신을 하였다. 이를 통해 로봇의 이동 정보를 실시간으로 취득할 수 있는 실내형 로봇 위치 추정 시스템을 구현하였다.

A Study on the Method for Capacity Estimation of Li-on Battery Pack Using Surrogate Model (근사 모델을 이용한 리튬이온 배터리팩 용량 추정에 대한 연구)

  • Kang, Deokhun;Park, Jin-Hyeng;Kim, Jonghoon
    • Proceedings of the KIPE Conference
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    • 2019.07a
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    • pp.420-421
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    • 2019
  • 리튬 이온 배터리는 전압, 전류, 온도 등의 측정 정보를 기반으로 용량, 수명 등 배터리의 상태를 추정해야 하며 이를 위해 다양한 방법들이 활용되고 있다. 이러한 추정 정보들은 결국 배터리 관리 시스템에서 수행하는 핵심 기능이며 효율적이고 안전한 제어를 수행하기 위해 필수적인 정보이다. 본 연구에서는 배터리 팩의 실험 데이터를 이용하여 근사 모델을 개발하고 이를 이용하여 배터리 팩의 용량을 추정하는 방법에 대한 연구를 수행하였다. 기존 수학적 모델 기반의 알고리즘을 활용하는 방법과 통계적인 기법을 활용하는 방법으로 구현하는 것과 달리, 충분한 데이터 확보가 가능한 경우, 데이터를 표현하는 근사 모델을 생성하고 이에 대한 활용 가능성을 확인하였다.

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SOC estimation of ESS for frequency regulation based on extended kalman filter (확장칼만필터 기반 주파수 조정용 ESS의 SOC 추정 연구)

  • Kwon, Soon-Jong;Choi, Jin Hyeok;Lim, Ji-Hun;Lee, Sung-Eun;Kim, Jonghoon
    • Proceedings of the KIPE Conference
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    • 2019.07a
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    • pp.201-203
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    • 2019
  • ESS의 데이터에 노이즈가 발생하였을 때 배터리의 상태를 정확하게 추정하는 것은 어려운 부분이며, 부정확한 배터리 상태 추정은 시스템의 안전성 및 신뢰성을 하락시킬 수 있다. 실제 사용되는 시스템의 대부분의 데이터에는 노이즈가 발생하며, 이러한 노이즈를 고려하여 배터리의 상태를 정확하게 파악하는 연구는 매우 중요하다. 본 논문에서는 주파수 조정 용도로 ESS가 사용되었을 때 배터리의 운전 패턴을 생성하고, 입력 데이터에 심각한 노이즈가 발생하였을 때 EKF 알고리즘을 사용하여 배터리의 상태를 정확하게 추정하는 것을 보여준다.

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Innovation and FDI: Applying Random Parameters Methods to KIS Data (기술혁신과 FDI)

  • Kim, Byung-Woo
    • Journal of Korea Technology Innovation Society
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    • v.13 no.3
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    • pp.513-537
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    • 2010
  • According to the "FDI-as-market-discipline" hypothesis, inward FDI acts as a mechanism of change in market structure affecting innovative activities of domestic firms. We used panel KIS data for testing this hypothesis. Binary probit estimation shows that, in contrast to the German case of Bertschek (1995), FDI is insignificant in Korean case for explaining product innovation. 1his result maybe comes from the fact that the industries in Korea are more monopolistic or oligopolistic than those of Germany. Using panel data, we tried random parameter estimation using matrix weighted average of GLS and OLS. The result shows different estimates from cross-section outcome and panel estimation with parameter homogeneity, so we can infer large parameter heterogeneity across firms. But, interpretation for FDI variable is similar across panel and cross-section estimation.

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Spatial Partitioning for Query Result Size Estimation in Spatial Databases (공간 데이터베이스에서 질의 결과 크기 추정을 위한 공간 분할)

  • 황환규
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.2
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    • pp.23-32
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    • 2004
  • The query optimizer's important task while a query is invoked is to estimate the fraction of records in the databases that satisfy the given query condition. The query result size estimation in spatial databases, like relational databases, proceeds to partition the whole input into a small number of subsets called “buckets” and then estimate the fraction of the input in the buckets. The accuracy of estimation is determined by the difference between the real data counts and approximations in the buckets, and is dependent on how to partition the buckets. Existing techniques for spatial databases are equi-area and equi-count techniques, which are respectively analogous in relation databases to equi-height histogram that divides the input value range into buckets of equal size and equi-depth histogram that is equal to the number of records within each bucket. In this paper we propose a new partitioning technique that determines buckets according to the maximal difference of area which is defined as the product of data ranges End frequencies of input. In this new technique we consider both data values and frequencies of input data simultaneously, and thus achieve substantial improvements in accuracy over existing approaches. We present a detailed experimental study of the accuracy of query result size estimation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. Experiments confirm that our proposed techniques offer better accuracy in query result size estimation than the existing techniques for space query size, bucket number, data number and data size.

임의 중단모형하에서의 평균잔여수명함수의 추정

  • Lee, In-Seok;Lee, U-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.2
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    • pp.45-57
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    • 1994
  • 이 연구에서는 Hjort(1991)에의해 제안된 누적위험률함수의 비모수적 추정량을 이용하여 무한인 구간까지 정의된 평균잔여수명함수의 추정량을 제안하고 제안된 추정량의 일치성과 점근적 정규성을 밝히고, 모의실험을 통하여 다른 추정량들과 비교하고자 한다.

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Approximation of Frequent Itemsets with Maximum Size by One-scan for Association Rule Mining Application (연관 규칙 탐사 응용을 위한 한 번 읽기에 의한 최대 크기 빈발항목 추정기법)

  • Han, Gab-Soo
    • The KIPS Transactions:PartD
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    • v.15D no.4
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    • pp.475-484
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    • 2008
  • Nowadays, lots of data mining applications based on continuous and online real time are increasing by the rapid growth of the data processing technique. In order to do association rule mining in that application, we have to use new techniques to find the frequent itemsets. Most of the existing techniques to find the frequent itemsets should scan the total database repeatedly. But in the application based on the continuous and online real time, it is impossible to scan the total database repeatedly. We have to find the frequent itemsets with only one scan of the data interval for that kind of application. So in this paper we propose an approximation technique which finds the maximum size of the frequent itemsets and items included in the maximum size of the frequent itemsets for the processing of association rule mining.

Covariance Matrix Estimation with Small STAP Data through Conversion into Spatial Frequency-Doppler Plane (적은 STAP 데이터의 공간주파수-도플러 평면 변환을 이용한 공분산행렬 추정)

  • Hoon-Gee Yang
    • Journal of IKEEE
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    • v.27 no.1
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    • pp.38-44
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    • 2023
  • Performance of a STAP(space-time adaptive processing) algorithm highly depends on how closely the estimated covariance matrix(CM) resembles the actual CM by the interference in CUT(cell under test). A STAP has 2 dimensional data structure determined by the number of array elements and the number of transmitting pulses and both numbers are generally not small. Thus, to meet the degree of freedom(DOF) of the CM, a huge amount of training data is required. This paper presents an algorithm to generate virtual training data from small received data, via converting them into the data in spatial frequency-Doppler plane. We theoretically derive where the clutter exist in the plane and present the procedure to implement the proposed algorithm. Finally, with the simulated scenario of small received data, we show the proposed algorithm can improve STAP performance.

Development of a Storage-Reliability Estimation Method Using Quantal Response Data for One-Shot Systems with Low Reliability-Decreasing Rates (미소한 신뢰도 감소율을 가지는 원샷 시스템의 가부반응 데이터를 이용한 저장 신뢰도 추정방법 개발)

  • Jang, Hyun-Jeung;Son, Young-Kap
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.10
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    • pp.1291-1298
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    • 2011
  • This paper proposes a new reliability estimation method for one-shot systems using quantal response data, which is based on a parametric estimation method. The proposed method considers the time-variant failure ratio of the quantal response data and it can overcome the problems in parametric estimation methods. Seven reliability estimation methods in the literature were compared with the proposed method in terms of the accuracy of reliability estimation in order to verify the proposed method. To compare the accuracy of reliability estimation, the SSEs (Sum of Squared Error) of the reliability estimation results for the different estimation methods were evaluated according to the various numbers of samples tested. The proposed method provided more accurate reliability estimation results than any of the other methods from the results of the accuracy comparison.

Wideband adaptive beamforming method using subarrays in acoustic vector sensor linear array (부배열을 이용한 음향벡터센서 선배열의 광대역 적응빔형성기법)

  • Kim, Jeong-Soo;Kim, Chang-Jin;Lee, Young-Ju
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.5
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    • pp.395-402
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    • 2016
  • In this paper, a wideband adaptive beamforming approach for an acoustic vector sensor linear array is presented. It is a very important issue to estimate the stable covariance matrix for adaptive beamforming. In the conventional wideband adaptive beamforming based on coherent signal-subspace (CSS) processing, the error of bearing estimates is resulted from the focusing matrix estimation and the large number of data snapshot is necessary. To alleviate the estimation error and snapshot deficiency in estimating covariance matrix, the steered covariance matrix method in the pressure sensor is extended to the vector sensor array, and the subarray technique is incorporated. By this technique, more accurate azimuth estimates and a stable covariance matrix can be obtained with a small number of data snapshot. Through simulation, the azimuth estimation performance of the proposed beamforming method and a wideband adaptive beamforming based on CSS processing are assessed.