• 제목/요약/키워드: Over-estimation

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A New Input Estimation Algorithm for Target Tracking Problem

  • Lee, Hungu;Tahk, Min-Jea
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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    • pp.323-328
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    • 1998
  • In this paper, a new input estimation algorithm is proposed for target tracking problem. The unknown target maneuver is approximated by a linear combination of independent time functions and the coefficients are estimated by using a weighted least-squares estimation technique. The proposed algorithm is verified by computer simulation of a realistic two-dimensional tracking problem. The proposed algorithm provides significant improvements in estimation performance over the conventional input estimation techniques based on the constant-input assumption.

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POT방법론을 이용한 자동차보험 손해율 추정 (Estimation of Car Insurance Loss Ratio Using the Peaks over Threshold Method)

  • 김수영;송종우
    • 응용통계연구
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    • 제25권1호
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    • pp.101-114
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    • 2012
  • 자동차보험의 손해율이란 지급보험금의 수입보험료에 대한 비율을 의미한다. 손해율이 매우 큰 값을 갖는 대형손실이 일어나는 경우에는 보험회사의 재무적인 부분에 큰 악영향을 미치게 된다. 따라서 보험회사가 이에 대비할 수 있도록 하기 위하여 손해율의 극단 분위수(extreme quantile)를 추정하는 것은 매우 중요한 일이다. 다른 종류의 보험 관련 데이터와 같이 손해율의 분포는 오른쪽으로 긴 꼬리를 갖는 두꺼운 꼬리분포(heavy-tailed distribution)를 갖는다. 이런 자료에서 극단 분위수룰 추정하기 위하여 가장 많이 사용되는 방법론은 POT(Peaks over threshold)와 Hill 추정(Hill estimation)이다. 본 논문에서는 일반화파레토분포(generalized Pareto distribution; GPD)의 다양한 모수추정방법론의 성능을 모의실험과 실제 손해율 데이터를 사용하여 비교, 분석하였다. 또한 Hill 추정치를 사용하여 극단 분위수를 추정하였다. 그 결과 대부분의 경우에 POT 방법론이 Hill 추정치를 이용한 방법보다 정확한 분위수를 추정하였고, 모수추정방법론 중에서는 MLE, Zhang, NLS-2 방법론이 가장 좋은 결과를 보여주었다.

Seismic damage estimation of reinforced concrete framed structures affected by chloride-induced corrosion

  • Anoop, M.B.;Rao, K. Balaji
    • Earthquakes and Structures
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    • 제9권4호
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    • pp.851-873
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    • 2015
  • A methodology for estimation of statistical properties (viz. mean and standard deviation) of the expected seismic damage to reinforced concrete framed structures subject to corrosion of reinforcement, over a specified reference time (typically the service life of the structure) is proposed in this paper. The damage to the structure under the earthquake loading is characterised by the damage index, determined using the modified Park and Ang damage model. The reduction in area, yield strength and strain at ultimate of steel reinforcement, and the reduction in compressive strength of cover concrete due to corrosion are taken into account in the estimation of damage. The proposed methodology is illustrated through an example problem. From the results obtained, it is noted that there is an increase of about 70% in the mean value of expected seismic damage to the reinforced concrete frame considered over a reference time of 30 years when effect of corrosion is taken into consideration. This indicates that there is a need to consider the effect of corrosion of reinforcement on the estimation of expected seismic damage.

Enhanced Timing Recovery Using Active Jitter Estimation for Voice-Over IP Networks

  • Kim, Hyoung-Gook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권4호
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    • pp.1006-1025
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    • 2012
  • Improving the quality of service in IP networks is a major challenge for real-time voice communications. In particular, packet arrival-delay variation, so-called "jitter," is one of the main factors that degrade the quality of voice in mobile devices with the voice-over Internet protocol (VoIP). To resolve this issue, a receiver-based enhanced timing recovery algorithm combined with active jitter estimation is proposed. The proposed algorithm copes with the effect of transmission jitter by expanding or compressing each packet according to the predicted network delay and variations. Additionally, the active network jitter estimation incorporates rapid detection of delay spikes and reacts to changes in network conditions. Extensive simulations have shown that the proposed algorithm delivers high voice quality by pursuing an optimal trade-off between average buffering delay and packet loss rate.

적응형 Unscented 칼만필터를 이용한 플러디드 납축전지의 SOC 추정 (SOC Estimation of Flooded Lead Acid Battery Using an Adaptive Unscented Kalman Filter)

  • 압둘바싯칸;최우진
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2016년도 추계학술대회 논문집
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    • pp.59-60
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    • 2016
  • Flooded lead acid batteries are still very popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation is of great importance for a flooded lead acid battery to ensure its safe working and to prevent it from over-charging or over-discharging. Different types of Kalman Filters are widely used for SOC estimation of batteries. The values of process and measurement noise covariance of a filter are usually calculated by trial and error method and taken as constant throughout the estimation process. While in practical cases, these values can vary as well depending upon the dynamics of the system. Therefore an Adaptive Unscented Kalman Filter (AUKF) is introduced in which the values of the process and measurement noise covariance are updated in each iteration based on the residual system error. A comparison of traditional and Adaptive Unscented Kalman Filter is presented in the paper. The results show that SOC estimation error by the proposed method is further reduced by 3 % as compared to traditional Unscented Kalman Filter.

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레이져 표면 경화 공정에서 신경회로망을 이용한 경화층 깊이 예측 (Estimation of Hardening Layer Depths in Laser Surface Hardening Processes Using Neural Networks)

  • 우현구;조형석;한유희
    • 한국정밀공학회지
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    • 제12권11호
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    • pp.52-62
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    • 1995
  • In the laser surface hardening process the geometrical parameters, especially the depth, of the hardened layer are utilized to assess the integrity of the hardening layer quality. Monitoring of this geometrical parameter ofr on-line process control as well as for on-line quality evaluation, however, is an extremely difficult problem because the hardening layer is formed beneath a material surface. Moreover, the uncertainties in monitoring the depth can be raised by the inevitable use of a surface coating to enhance the processing efficiency and the insufficient knowledge on the effects of coating materials and its thicknesses. The paper describes the extimation results using neural network to estimate the hardening layer depth from measured surface temperanture and process variables (laser beam power and feeding velocity) under various situations. To evaluate the effec- tiveness of the measured temperature in estimating the harding layer depth, estimation was performed with or without temperature informations. Also to investigate the effects of coating thickness variations in the real industry situations, in which the coating thickness cannot be controlled uniform with good precision, estimation was done over only uniformly coated specimen or various thickness-coated specimens. A series of hardening experiments were performed to find the relationships between the hardening layer depth, temperature and process variables. The estimation results show the temperature informations greatly improve the estimation accuracy over various thickness-coated specimens.

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지구통계 기법을 활용한 토양 오염범위 산정 및 불확실성 평가 (Evaluation of Geostatistical Approaches for better Estimation of Polluted Soil Volume with Uncertainty Evaluation)

  • 김호림;김경호;윤성택;황상일;김형돈;이군택;김영주
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제17권6호
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    • pp.69-81
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    • 2012
  • Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

A data-adaptive maximum penalized likelihood estimation for the generalized extreme value distribution

  • Lee, Youngsaeng;Shin, Yonggwan;Park, Jeong-Soo
    • Communications for Statistical Applications and Methods
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    • 제24권5호
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    • pp.493-505
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    • 2017
  • Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

An Efficient Global Motion Estimation based on Robust Estimator

  • Joo, Jae-Hwan;Choe, Yoon-Sik
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.408-412
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    • 2009
  • In this paper, a new efficient algorithm for global motion estimation is proposed. This algorithm uses a previous 4-parameter model based global motion estimation algorithm and M-estimator for improving the accuracy and robustness of the estimate. The first algorithm uses the block based motion vector fields and which generates a coarse global motion parameters. And second algorithm is M-estimator technique for getting precise global motion parameters. This technique does not increase the computational complexity significantly, while providing good results in terms of estimation accuracy. In this work, an initial estimation for the global motion parameters is obtained using simple 4-parameter global motion estimation approach. The parameters are then refined using M-estimator technique. This combined algorithm shows significant reduction in mean compensation error and shows performance improvement over simple 4-parameter global motion estimation approach.

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A Joint Channel Estimation and Data Detection for a MIMO Wireless Communication System via Sphere Decoding

  • Patil, Gajanan R.;Kokate, Vishwanath K.
    • Journal of Information Processing Systems
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    • 제13권4호
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    • pp.1029-1042
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    • 2017
  • A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.