• Title/Summary/Keyword: time-series observation

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Time-series Analysis and Prediction of Future Trends of Groundwater Level in Water Curtain Cultivation Areas Using the ARIMA Model (ARIMA 모델을 이용한 수막재배지역 지하수위 시계열 분석 및 미래추세 예측)

  • Baek, Mi Kyung;Kim, Sang Min
    • Journal of The Korean Society of Agricultural Engineers
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    • v.65 no.2
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    • pp.1-11
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    • 2023
  • This study analyzed the impact of greenhouse cultivation area and groundwater level changes due to the water curtain cultivation in the greenhouse complexes. The groundwater observation data in the Miryang study area were used and classified into greenhouse and field cultivation areas to compare the groundwater impact of water curtain cultivation in the greenhouse complex. We identified the characteristics of the groundwater time series data by the terrain of the study area and selected the optimal model through time series analysis. We analyzed the time series data for each terrain's two representative groundwater observation wells. The Seasonal ARIMA model was chosen as the optimal model for riverside well, and for plain and mountain well, the ARIMA model and Seasonal ARIMA model were selected as the optimal model. A suitable prediction model is not limited to one model due to a change in a groundwater level fluctuation pattern caused by a surrounding environment change but may change over time. Therefore, it is necessary to periodically check and revise the optimal model rather than continuously applying one selected ARIMA model. Groundwater forecasting results through time series analysis can be used for sustainable groundwater resource management.

Study of Active Galactic Nuclei and Gravitational Wave Sources with Time-series Observation

  • Kim, Joonho;Im, Myungshin
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.2
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    • pp.39.1-39.1
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    • 2021
  • In this presentation, study of the energetic astronomical phenomena, active galactic nucleus (AGN) and gravitational wave (GW) source, with time-series observation will be reported. They emit large amounts of energy and play an important role in the history of the Universe. First, intra-night variability of AGNs is studied using Korea Microlensing Telescope Network (KMTNet). Second topic is photometric reverberation mapping which is applied for 11 AGNs with medium-bands and Lee Sang Gak Telescope. Last, three gravitational wave events were followed-up by various optical telescopes. Each topic will be specifically addressed in the presentation.

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Comparison of prediction methods for Nonlinear Time series data with Intervention1)

  • Lee, Sung-Duck;Kim, Ju-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.265-274
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    • 2003
  • Time series data are influenced by the external events such as holiday, strike, oil shock, and political change, so the external events cause a sudden change to the time series data. We regard the observation as outlier that occurred as a result of external events. In general, it is called intervention if we know the period and the reason of external events, and it makes an analyst difficult to establish a time series model. Therefore, it is important that we analyze the styles and effects of intervention. In this paper, we considered the linear time series model with invention and compared with nonlinear time series models such as ARCH, GARCH model and also we compared with the combination prediction method that Tong(1990) introduced. In the practical case study, we compared prediction power with RMSE among linear, nonlinear time series model with intervention and combination prediction method.

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The Evaluation of the Annual Time Series Data for the Mean Sea Level of the West Coast by Regression Model (회귀모형에 의한 서해안 평균해면의 연시계열자료의 평가)

  • 조기태;박영기;이장춘
    • Journal of Environmental Science International
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    • v.9 no.1
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    • pp.19-25
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    • 2000
  • As the tideland reclamation is done on a large scale these days, construction work is active in the coastal areas. Facilities in the coastal areas must be built with the tide characteristics taken into consideration. Thus the tide characteristics affect the overall reclamation plan. The analysis of the tide data boils down to a harmonic analysis of the hourly changes of long-term tide data and extraction of unharmonic coefficients from the results. Since considerable amount of tide data of the West Coast are available, the existing data can be collected and can be used to obtain the temporal changes of the tide by being fitted into the tide prediction model. The goal of this thesis lies in assessing whether the mean sea level used in the field agrees with the analysis results from the long-term observation data obtained with their homogeneity guaranteed. To achieve this goal, the research was conducted as follows. First the present conditions of the observation stations, the land level standard, and the sea level standard were analyzed to set up a time series model formula for representing them. To secure the homogeneity of the time series, each component was separated. Lastly the mean sea level used in the field was assessed based on the results obtained form the analysis of the time series.

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On A New Framework of Autoregressive Fuzzy Time Series Models

  • Song, Qiang
    • Industrial Engineering and Management Systems
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    • v.13 no.4
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    • pp.357-368
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    • 2014
  • Since its birth in 1993, fuzzy time series have seen different classes of models designed and applied, such as fuzzy logic relation and rule-based models. These models have both advantages and disadvantages. The major drawbacks with these two classes of models are the difficulties encountered in identification and analysis of the model. Therefore, there is a strong need to explore new alternatives and this is the objective of this paper. By transforming a fuzzy number to a real number via integrating the inverse of the membership function, new autoregressive models can be developed to fit the observation values of a fuzzy time series. With the new models, the issues of model identification and parameter estimation can be addressed; and trends, seasonalities and multivariate fuzzy time series could also be modeled with ease. In addition, asymptotic behaviors of fuzzy time series can be inspected by means of characteristic equations.

Adaptive Reconstruction of Multi-periodic Harmonic Time Series with Only Negative Errors: Simulation Study

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.26 no.6
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    • pp.721-730
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    • 2010
  • In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

Time Series Analysis of Groundwater Level Change in the Chuncheon Area Groundwater Observation Network (시계열 분석을 이용한 춘천 지역 지하수관측망 수위변동 해석)

  • Mok, Jong-Koo;Jang, Bum-Ju;Park, Yu-Chul;Shin, Hye-Soo;Kim, Jin-Ho;Song, Se-Jeong;Hawng, Ga-Young
    • The Journal of Engineering Geology
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    • v.32 no.2
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    • pp.281-293
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    • 2022
  • Time series analysis was performed on data from 2009 to 2018 from the Chuncheon groundwater observation network to understand the characteristics of groundwater level fluctuations in the network. There are five observatories, all of which are installed in rock aquifers, and periodic inspections and management are performed by the relevant operating organization. Auto-correlation, spectral density, and cross-correlation analysis was performed.

Development of a Period Analysis Algorithm for Detecting Variable Stars in Time-Series Observational Data

  • Kim, Dong-Heun;Kim, Yonggi;Yoon, Joh-Na;Im, Hong-Seo
    • Journal of Astronomy and Space Sciences
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    • v.36 no.4
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    • pp.283-292
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    • 2019
  • The purpose of this study was to develop a period analysis algorithm for detecting new variable stars in the time-series data observed by charge coupled device (CCD). We used the data from a variable star monitoring program of the CBNUO. The R filter data of some magnetic cataclysmic variables observed for more than 20 days were chosen to achieve good statistical results. World Coordinate System (WCS) Tools was used to correct the rotation of the observed images and assign the same IDs to the stars included in the analyzed areas. The developed algorithm was applied to the data of DO Dra, TT Ari, RXSJ1803, and MU Cam. In these fields, we found 13 variable stars, five of which were new variable stars not previously reported. Our period analysis algorithm were tested in the case of observation data mixed with various fields of view because the observations were carried with 2K CCD as well as 4K CCD at the CBNUO. Our results show that variable stars can be detected using our algorithm even with observational data for which the field of view has changed. Our algorithm is useful to detect new variable stars and analyze them based on existing time-series data. The developed algorithm can play an important role as a recycling technique for used data

Sustainable Surface Deformation Related with 2006 Augustine Volcano Eruption in Alaska Measured Using GPS and InSAR Techniques

  • Lee, Seulki;Kim, Sukyung;Lee, Changwook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.4
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    • pp.357-372
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    • 2016
  • Augustine volcano, located along the Aleutian Arc, is one of the most active volcanoes in Alaska and nearby islands, with seven eruptions occurring between 1812 and 2006. This study monitored the surface displacement before and after the most recent 2006 eruption. For analysis, we conducted a time-series analysis on data observed at the permanent GPS(Global Positioning System) observation stations in Augustine Island between 2005 and 2011. According to the surface displacement analysis results based on GPS data, the movement of the surface inflation at the average speed of 2.3 cm/year three months prior to the eruption has been clearly observed, with the post-eruption surface deflation at the speed of 1.6 cm/year. To compare surface displacements measurement by GPS observation, ENVISAT(Environmental satellite) radar satellite data were collected between 2003 and 2010 and processed the SBAS(Small Baseline Subset) method, one of the time-series analysis techniques using multiple InSAR(Interferometric Synthetic Aperture Radar) data sets. This result represents 0.97 correlation value between GPS and InSAR time-series surface displacements. This research has been completed precise surface deformation using GPS and time-series InSAR methods for a detection of precursor symptom on Augustine volcano.

A Study on the Characteristics of Change by Observation Area which changes as the observation time passes in Interior Space (실내공간에서 주시시간의 경과에 따른 구역별 주시특성에 관한 연구)

  • Kim, Jong-Ha;Ban, Young-Sun
    • Korean Institute of Interior Design Journal
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    • v.21 no.2
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    • pp.84-91
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    • 2012
  • The total data of observing interior space was divided into a few time frames for analysis. If we can understand the changing process of observation degree as the observation time passes, we will be able to analyse the characteristic and process of information obtainment in the case of space observation. For this purpose, the observation time was parted into 30 second units and the changing characteristic by time frame and observation area was analysed. The conclusion derived from this study is as the following: First, analysis of observation frequency and time on the basis of the average data of each subject showed that the observation time increased compared with the subject's frequency and the overall trend but that it was difficult for me to think there was a certain trend in the observation time of each subject. However, when I examined the time change by using the trend line which is a dynamic average line representing the observation time from the subjects as the trend element of time series, I could see the trend that the subject's observation time increased at a fixed rate as the frequency increased. Second, when I compared and analysed the average observation area at Area I set up by the time of 30 second unit and the observation area of Area I from the all data, I could see that the former had more degree of concentration at Area I. This analysis enabled me to get the degree of concentration on the observed area every time, and accordingly I could also see that when the data of intensive observation by time frame is analysed, the degree of concentration is dispersed for the subjects to observe very intensively or the area with overlapping observations each time frame can be seen as Area I out of the entire observation data. Third, when I analysed the observation characteristics by time frame at the 6 areas divided at 30 second unit at the rate of the number to the time of observation areas, I could see that as the observation time passed while the number of the observation areas defined as decreased the observation time increased, which means that when the area numbers decreases the area intensively observed by the subjects decreases as the time passes. In spit of that, the increase of time can be interpreted as more intensive observation of a specific area.

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