• Computational Structural Engineering
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• v.3 no.4
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• pp.143-148
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the auto regressive and moving average model with auxiliary stochastic input(ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story budding model subject to ground exitations.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

• Computational Structural Engineering
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• v.3 no.4
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• pp.10-13
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• 1990

구조물의 동적계수 추정방법과 이에 관련된 몇가지 사항들에 대해서 기술하였다. 여러 문제들중 가장 중요한 것이라고 생각되는 것으 소음에 대한 처리문제라고 여겨진다. 순차적 예측오차법과 같은 비선형 최적화기법을 사용하여 측정오차와 관련된 소음영향은 어느정도 처리되어질 수 있다고 생각되나, 많은 자유도를 가진 실제구조물의 거동을 간단한 모형식으로 나타냄으로써 야기되는 모형화 오차에 대해서는 아직 그 처리방법에 상당한 난점이 있다. 앞으로 이에 대한 많은 연구가 요구되는 실정이다.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.457-464
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• 2009

This paper proposes methodologies for analyzing the accuracy of the proportional hazards model in predicting consecutive break times of water mains and estimating the time interval for economical water main replacement. By using the survival functions that are based on the proportional hazards models a criterion for the prediction of the consecutive pipe breaks is determined so that the prediction errors are minimized. The criterion to predict pipe break times are determined as the survival probability of 0.70 and only the models for the third through the seventh break are analyzed to be reliable for predicting break times for the case study pipes. Subsequently, the criterion and the estimated lower and upper bound survival functions of consecutive breaks are used in predicting the lower and upper bounds of the 95% confidence interval of future break times of an example water main. Two General Pipe Break Prediction Models(GPBMs) are estimated for an example pipe using the two series of recorded and predicted lower and upper bound break times. The threshold break rate is coupled with the two GPBMs and solved for time to obtain the economical replacement time interval.

• The Journal of the Acoustical Society of Korea
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• v.11 no.1E
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• pp.73-78
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• 1992

시벼형 신호인 음성 신호의 분석에 칼만필터를 이용하였다. 일반적인 음성 분석은 프레임단위의 처리방법인 선형 예측 부호화 기법을 주로 이용하지만 음성의 시변 특성을 파악하는데에는 적절하지 못 하다. 따라서 순차적인 추정기법으로 많이 이용되는 칼만 필터를 음성 분석에 적용하였다. 또한 음성과 같은 시변신호에서는 과거 신호의 잡음의 분산값에 적당한 가중치를 부가하므로써 과거의 신호에 의해 서 현재의 추정값에 미치는 영향을 줄였으며 이를 음성의 천이 구간에서의 파라메타 추정에 사용하였 다. 그리고 음성신호 모델에서 생기는 모델링 오차는 일반적으로 백색 가우시안 잡음으로 가정하고 있 으나 이는 자음과 같은 무성음에서 특징 파라메타 푸정에는 오차가 적지만 모음등의 유성음에서는 음성 발생시의 여기신호인 펄스열에 의해서 많은 모델링 오차를 생기게 한다. 따라서 모델링 오차신호는 Non-Gaussian 확률분포로 가정한 후 로버스트 칼만 필터를 사용하여 합성으멩 대해 특징 파라메터를 추출하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.79-84
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the autoregressive and moving average model with auxiliary stochastic input (ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then, the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story building model subject to ground exitations.

• Computational Structural Engineering
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• v.7 no.4
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• pp.137-144
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• 1994

As for the safety evaluation of existing large-scale structures, methods for the estimation of structural and dynamic properties are studied. Sequential prediction error method in time domain and frequency response function estimators in frequency domain are examined. For this purpose, impact tests are performed on a steel frame structure with 2 bays and 3 floors. Results from both methods are found to be consistent to each others. However those from the finite-element analysis are slightly different from the experimental results. The discrepancies may be caused by the improper modeling of the complex behavior at the connection joints of the model structure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.458-459
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• 2021

Recently, researches using deep learning technology based on Wi-Fi fingerprints have been conducted for accurate services in indoor location-based services. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. At this time, continuous sequential data is required as training data. However, since Wi-Fi fingerprint data is generally managed only with signals for a specific location, it is inappropriate to use it as training data for an RNN model. This paper proposes a path generation method through prediction of a moving path based on Wi-Fi fingerprint data extended to region data through clustering to generate sequential input data of the RNN model.

• The KIPS Transactions:PartA
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• v.12A no.3 s.93
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• pp.243-252
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• 2005

This paper introduces a noble modeling technique to build data communication prediction models in multiprocessors, using Least-Squares and Robust Estimation methods. A set of sample communication rates are collected by using a few small input data sets into workload programs. By applying estimation methods to these samples, we can build analytic models that precisely estimate communication rates for huge input data sets. The primary advantage is that, since the models depend only on data set size not on the specifications of target systems or workloads, they can be utilized to various systems and applications. In addition, the fact that the algorithmic behavioral characteristics of workloads are reflected into the models entitles them to model diverse other performance metrics. In this paper, we built models for cache miss rates which are the main causes of data communication in shared memory multiprocessor systems. The results present excellent prediction error rates; below $1\%$ for five cases out of 12, and about $3\%$ for the rest cases.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.59-64
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• 2011

In this paper, the lumped element model parameter estimation method and its implemented estimation software for fabricated floating mass transducers of IMEHDs have been presented so that the estimated parameter values could be compared with the designed ones and applied to predict the output performance when the transducers were implanted into human ears. The presented method is based on the sequential quadratic programming (SQP) for estimating parameters in the transducer's lumped model and has been implemented by the use of LabVIEW graphical language. Using the implemented estimation software, the accuracy of parameter estimation has been verified and our implemented estimation method has been evaluated by the comparison of the estimated transducer parameter values with the designed ones for a practically fabricated floating mass transducer for IMEHDs.