• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.883-887
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• 2009

본 논문은 AR(P) 입력에 대해 MPDSAP 알고리즘의 적응과정의 MSE의 통계적 분석을 제시한다. 부밴드 구조에서 인접투사 알고리즘은 적응필터에 다위상 분해와 노블아이덴티티를 적용함으로써 NLMS 알고리즘으로 변환된다. 또한, P차의 Autoregressive(AR) 입력은 정규직교 분해필터에 의해 사전에 백색화 될 수 있다. 부밴드 구조에서 AR(P) 입력의 사전-백색화(pre-whitening)는 SAP 적응필터의 MSE 행동의 통계적 해석을 위한 간단하고 유효한 근사화를 제공한다.

• 대한전자공학회논문지SP
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• 제46권6호
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• pp.163-174
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• 2009

부밴드 구조에서 적응필터에 최대 다위상 분해와 노블아이덴티티를 적용함으로써 전밴드 인접투사 알고리즘은 부밴드 인접투사 알고리즘으로 변환된다. 최대 다위상 분해된 부밴드 인접투사 (Maximally Polyphase Decomposed Subband Affine Projection: MPDSAP) 알고리즘은 각 부밴드의 적응 부필터에서 사용되는 투사차원이 1인 부밴드 인접투사 알고리즘의 특별한 형태다. MPDSAP 알고리즘의 계수갱신식은 NLMS 알고리즘과 유사한 형식을 갖기 때문에 실제 구현관점에서 보다 좋은 알고리즘 선택이 될 수 있다. 본 논문은 MPDSAP 알고리즘의 새로운 통계적 해석을 제시한다. 해석적 모델은 정규직교 분해필터를 갖는 부밴드 구조에서 Autoregressive (AR) 입력과 임의의 적응이득에 대해 유도된다. 정규직교 분해필터에 의한 사전 백색화는 AR 입력과 임의의 적응이득에 대한 MPDSAP 알고리즘의 간단한 해석적 모델의 유도를 가능하게 한다.

• 한국환경과학회지
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• 제26권10호
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• pp.1135-1146
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• 2017

At riverbank filtration sites, groundwater levels of alluvial aquifers near rivers are sensitive to variation in river discharge and pumping quantities. In this study, the groundwater level fluctuation, pumping quantity, and streamflow rate at the site of a riverbank filtration plant, which produces drinking water, in the lower Nakdong River basin, South Korea were interrelated. The relationship between drawdown ratio and river discharge was very strong with a correlation coefficient of 0.96, showing a greater drawdown ratio in the wet season than in the dry season. Autocorrelation and cross-correlation were carried out to characterize groundwater level fluctuation. Autoregressive model analysis of groundwater water level fluctuation led to efficient estimation and prediction of pumping for riverbank filtration in relation to river discharge rates, using simple inputs of river discharge and pumping data, without the need for numerical models that require data regarding several aquifer properties and hydrologic parameters.

• 응용통계연구
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• 제37권3호
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• pp.297-309
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• 2024

본 논문에서는 자기회귀 신경망 모형과 지수평활법을 결합(NNARX+ETS 모형)하고 그 성능을 평가한다. 제안된 결합 모형은 시계열 자료를 예측하기 위하여 NNARX 모형의 외생변수로서 ETS 모형의 구성 성분을 활용한다. 이 모형의 주요 아이디어는, 신경망 모형이 원시계열 자료의 과거 시차만을 고려하는 것을 한계를 넘어서서 전통적 시계열 예측 방법인 지수평활법에 의해서 추출된 정제된 시계열 구성 성분까지도 추가로 신경망 모형의 입력값으로 사용하는 것이다. 예측 성능 평가는 2가지 실제 시계열 자료를 사용하였으며 제안된 모형을 NNAR 모형 및 전통적 시계열 분석 방법인 ETS와 ARIMA 모형과 비교하였다.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.702-708
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• 2019

This paper deals with break size estimation of loss of coolant accidents (LOCA) using a nonlinear autoregressive with exogenous inputs (NARX) neural network. Previous studies used static approaches, requiring time-integrated parameters and independent firing algorithms. NARX neural network is able to directly deal with time-dependent signals for dynamic estimation of break sizes in real-time. The case studied is a LOCA in the primary system of Bushehr nuclear power plant (NPP). In this study, number of hidden layers, neurons, feedbacks, inputs, and training duration of transients are selected by performing parametric studies to determine the network architecture with minimum error. The developed NARX neural network is trained by error back propagation algorithm with different break sizes, covering 5% -100% of main coolant pipeline area. This database of LOCA scenarios is developed using RELAP5 thermal-hydraulic code. The results are satisfactory and indicate feasibility of implementing NARX neural network for break size estimation in NPPs. It is able to find a general solution for break size estimation problem in real-time, using a limited number of training data sets. This study has been performed in the framework of a research project, aiming to develop an appropriate accident management support tool for Bushehr NPP.

• 대한토목학회논문집
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• 제38권5호
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• pp.671-683
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• 2018

도시유역에 대한 집중호우에 따른 침수피해가 증가하고 있으며, 기존에 수행된 많은 연구에서 입증 되어진 바와 같이 도시 침수는 하수관망의 통수능을 상회함에 따라 발생하는 내수침수에 주로 기인하고 있다. 도시화가 상당히 진행되고 인구가 밀집되어 있는 지역에 대한 침수피해는 심각한 사회 경제적 피해를 야기한다. 이에 따라 도시지역에 대한 홍수 예측을 위한 확정 및 확률론적 연구가 진행되어 왔지만, 충분한 선행시간을 확보하며 단시간에 홍수량에 대한 예측결과를 도출하기에는 부족한 실정이다. 본 연구에서는 최적의 실시간 도시 홍수 예측 기법을 제시하기 위하여 도시유출해석 기반 실시간 홍수 예측을 위한 IDNN, TDNN 그리고 NARX 동적신경망을 비교하였다. 강남 지역의 2010, 2011년 실제 호우사상에 대하여 총 홍수량 예측 결과, 입력 지연 인공신경망의 최대 Nash-Sutcliffe 효율 계수는 각각 0.86, 0.53, 시간 지연 인공신경망의 경우 0.92, 0.41, 외생변수를 이용한 비선형 자기 회귀의 경우 0.99, 0.98으로 나타났다. 연구 대상지역에 대한 각 맨홀 누적월류량을 고려한 예측 결과의 오차분석을 통하여 외생변수를 이용한 비선형 자기 회귀 기법을 사용하는 것이 추후 도시 홍수 대응체계 구축에 적합할 것으로 나타났다.

• 비파괴검사학회지
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• 제36권2호
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• pp.93-101
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• 2016

This paper presents the results obtained using time-series-based methods for structural damage assessment. The methods are applied to a wind turbine blade structure subjected to fatigue loads. A 9 m CX-100 (carbon experimental 100 kW) blade is harmonically excited at its first natural frequency to introduce a failure mode. Consequently, a through-thickness fatigue crack is visually identified at 8.5 million cycles. The time domain data from the piezoelectric active-sensing techniques are measured during the fatigue loadings and used to detect incipient damage. The damage-sensitive features, such as the first four moments and a normality indicator, are extracted from the time domain data. Time series autoregressive models with exogenous inputs are also implemented. These features could efficiently detect a fatigue crack and are less sensitive to operational variations than the other methods.

• 동아시아경상학회지
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• 제6권4호
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• pp.35-45
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• 2018

Purpose - The operating mechanism between education input and economic growth is a mysterious proposition that has attracted a vast array of scholars' interests to study on it. Therefore, this paper sets China as an example to analyze the dynamic relationship between education input and economic growth. Research design and methodology - The annual time series from 1990 to 2017 will be employed to conduct an empirical analysis under the vector autoregressive model. The education input is treated as an factor that impacts the economic growth such as labor input and capital input. Meanwhile, the education input will be added to the Cobb-Douglas production function to form a new one so as to explore the dynamic relationship between education input and economic growth. Results - According to the results of empirical analysis, it can be found that the education input has an increasingly positive effect on economic growth. Simultaneously, the economic growth also has a positive effect on education input, but this kind of effect is not steady. Of course, the labor input and the capital input also can promote the economic growth to some degree. Conclusions - The education input is one of most important inputs for a country. Based on the empirical analysis, this paper suggests that the China's government should put more emphasis on the education input so to make its economy develop well.

• Smart Structures and Systems
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• 제4권6호
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• pp.759-777
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• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.400-407
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• 2022

Innovations significantly affect the efficiency of the socioeconomic systems of the regions, acting as a system-forming element of their development. Modern models of economic development also consider innovation activity, intellectual potential, knowledge as the basic factors for stimulating the economic growth of the region. The purpose of the study is to develop methodological foundations for evaluating the effectiveness of a regional innovation system based on a multidimensional analysis of its effects. To further study the effectiveness of RIS, we have used one of the methods of multidimensional statistical analysis - canonical analysis. The next approach allows adding another important requirement to the methodological provision of evaluation of the level of innovation development of industries and regions, namely - the time factor, the formalization of which is realized in autoregressive dynamic economic and mathematical models and can be used in our research. Multidimensional Statistical Analysis for RIS effectiveness estimation was used to model RIS by typological regression. Based on it, multiple regression models were built in groups of regions with low and relatively high innovation potential. To solve the methodological problem of RIS research, we can also use the approach to the system as a "box" with inputs and outputs.