• International journal of advanced smart convergence
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• 제10권4호
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• pp.98-103
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• 2021

Recently, as the need for food resources has increased both domestically and internationally, support for the agricultural sector for stable food supply and demand is expanding in Korea. However, according to recent media articles, the biggest problem in rural communities is the unstable profit structure. In addition, in order to confirm the profit structure, profit forecast data must be clearly prepared, but there is a lack of auxiliary data for farmers or future returnees to predict farm income. Therefore, in this paper we analyzed data over the past 15 years through time series analysis and proposes an artificial intelligence farm income prediction algorithm that can predict farm household income in the future. If the proposed algorithm is used, it is expected that it can be used as auxiliary data to predict farm profits.

• 디지털융복합연구
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• 제15권12호
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• pp.333-340
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• 2017

실시간검색어는 지금 바로 이슈가 되는 검색어의 검색 증가율이 단기간에 급상승하는 것을 중심으로 하기 때문에 일정기간 지속적으로 관심도를 유지하고 있는 이슈를 나타내지 못하고 이들이 가까운 미래에 어떤 변화를 보이는지에 대한 것도 알 수 없는 한계를 가지고 있다. 본 논문에서는 이러한 한계를 극복할 수 있도록 일정기간 동안 상위 10위 안에 속한 적이 있는 실시간검색어에 대해 일자별, 시간별 지속성을 평가하여 꾸준히 관심을 받는 검색어를 추출한다. 그런 다음, 이들 중 상위에 속하는 검색어의 관심도가 어떻게 변화하는지를 알 수 있게 하는 시계열 분석과 신경망을 이용하는 방법을 제시하고 이를 통해 도출한 실제 예를 통해 가까운 미래의 변화량을 예측한 결과를 보인다. 일자별로는 시계열 분석을, 시간별로는 인공신경망의 학습을 통해 예측하는 것이 좋은 결과를 보인다는 것을 알 수 있다.

• 전기학회논문지P
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• 제53권4호
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• pp.175-182
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• 2004

This paper presents a new method for finding the Block Pulse series coefficients, deriving the Block Pulse integration operational matrices and generalizing the integration operational matrices which are necessary for the control fields using the Block Pulse functions. In order to apply the Block Pulse function technique to the problems of state estimation or parameter identification more efficiently, it is necessary to find the more exact value of the Block Pulse series coefficients and integral operational matrices. This paper presents the method for improving the accuracy of the Block Pulse series coefficients and derives generalized integration operational matrix and applied the matrix to the analysis of linear time-invariant system.

• 한국측량학회지
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• 제25권6_1호
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• pp.537-543
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• 2007

Since the GPS absolute positioning with pseudorange measurements can significantly be affected by the observation error, the time series analysis of the GPS receiver clock errors was performed in this study. From the estimated receiver clock errors, the time series model is generated, and constrained back in the absolute positioning process. One of the CORS (Continuously Operating Reference Stations) network is used to analyze the behavior of the receiver clock. The dominant part of the model is the linear trend during 24 hours, and the seasonal component is also estimated. After constraining the modeled receiver clock errors, the estimated position error compared to the published coordinates is improved from ${\pm}11.4\;m\;to\;{\pm}9.5\;m$ in 3D RMS.

• 상하수도학회지
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• 제18권6호
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• pp.758-769
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• 2004

The trends and seasonalities of most time series have a large variability. The result of the Singular Spectrum Analysis(SSA) processing is a decomposition of the time series into several components, which can often be identified as trends, seasonalities and other oscillatory series, or noise components. Generally, forecasting by the SSA method should be applied to time series governed (may be approximately) by linear recurrent formulae(LRF). This study examined forecasting ability of SSA-LRF model. These methods are applied to daily water demand data. These models indicate that most cases have good ability of forecasting to some extent by considering statistical and visual assessment, in particular forecasting validity shows good results during 15 days.

• Journal of Welding and Joining
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• 제18권1호
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• pp.97-103
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• 2000

Time series analysis results show the SVD is a candidate of on-line monitoring of welding penetration when the covariance matrix of a full penetration is used as a mapping function. As the reconstructed embedding vectors from the chaotic scalar time series are manipulated by the covariance matrix, the mapped tim series lie on a hyper-ellipsoid which the lengths of semi-axes are the squared eigenvalues of the covariance matrix in the case of full penetration. These visualize by two dimensional stroboscope views. The other cases like partial penetration, are different in the sense of sizes and shapes. Here we test two types of time series; the ion current and the X-ray. The ion current is better than the X-ray as an on-line monitoring signal, because the difference of the eigenvalue spectrum of the ion(between the pull penetration and partial penetration) is bigger than those of the X-ray.

• 한국측량학회지
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• 제28권3호
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• pp.361-367
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• 2010

이 연구에서는 국토지리정보원 14개 GPS 상시관측소에서 수집된 약 5년간의 GPS 자료를 고정밀 처리하여 연속적인 수직좌표 시계열을 생성하였다. 그리고 1차 선형회귀식을 사용하여 GPS 상시관측소 속도를 계산하였으며, GPS 수직좌표 변동 경향을 분석하기 위해 주성분분석을 실시하였다. 가장 우세한 성분의 신호를 나타내는 모드 1을 대상으로 분석한 결과 약 4.2mm/yr의 수직 속도가 산출되었다. 그리고 모드 1의 고유 벡터 값에서 일관성을 보였다. 따라서 분석대상 기간 동안에는 모든 관측소가 일제히 상승하는 신호를 보이고 있음을 알 수 있었다. 또한 14개 GPS 상시관측소 시계열에서 주성분분석을 통해 산출된 모드 1 신호를 제거하고 모드 1의 신호 제거 전 후에 따른 관측소 수직좌표 시계열의 정밀도 변화를 분석하였다. 그 결과, 수직좌표 시계열의 정밀도는 평균 34.8% 향상되었다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2000년도 추계학술발표회 논문집
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• pp.13-15
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• 2000

In this paper, we deal with the asymptotic properties of the regression quantile estimators in the nonlinear time series regression model. For the sinusodial model which frequently appears fer a time series analysis, we study the strong consistency and asymptotic normality of regression quantile ostinators.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.279-285
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• 2002

In this paper we consider the problem of testing for structural changes in ARIMA models based on a cusum test. In particular, the proposed test procedure is applicable to testing for a change of the status of time series from stationarity to nonstationarity or vice versa. The idea is to transform the time series via differencing to make stationary time series. We propose a graphical method to identify the correct order of differencing.

• Journal of the Korean Statistical Society
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• 제29권2호
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• pp.187-199
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• 2000

In this paper, we deal with the asymptotic properties of the least absolute deviation estimators in the nonlinear time series regression model. For the sinusodial model which frequently appears in a time series analysis, we study the strong consistency and asymptotic normality of least absolute deviation estimators. And using the derived limiting distributions we show that the least absolute deviation estimators is more efficient than the least squared estimators when the error distribution of the model has heavy tails.