• 제목/요약/키워드: Time Series Changes

검색결과 815건 처리시간 0.027초

Time Series Data Cleaning Method Based on Optimized ELM Prediction Constraints

  • Guohui Ding;Yueyi Zhu;Chenyang Li;Jinwei Wang;Ru Wei;Zhaoyu Liu
    • Journal of Information Processing Systems
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    • 제19권2호
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    • pp.149-163
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    • 2023
  • Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.

전도 시계열 계수를 수치해석으로 구하는 방법 (A Procedure for Computing Conduction Time Series Factors by Numerical Method)

  • 변기홍
    • 한국태양에너지학회 논문집
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    • 제37권5호
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    • pp.77-84
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    • 2017
  • The purpose of this paper is to propose the way of computing conduction time series factors (CTSF) using numerical method. After the accuracy of the numerical solution procedure being verified, the method is applied to the wall type 24 and roof type 14 of ASHARE to find the conduction time series coefficients, so called conduction time series factors. The results agree well with the values presented in the ASHRAE handbook. The method proposed can be easily applied to find unknown CTSF for more complex structures. It provides information about the temperature changes at a given location and time, thus validity of generated CTSF can be checked easily.

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

  • 조기태;박영기;이장춘
    • 한국환경과학회지
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    • 제9권1호
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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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Test for Structural Change in ARIMA Models

  • 이상열;박시연
    • 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.

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The Change Point Analysis in Time Series Models

  • Lee, Sang-Yeol
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.43-48
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    • 2005
  • We consider the problem of testing for parameter changes in time series models based on a cusum test. Although the test procedure is well-established for the mean and variance in time series models, a general parameter case has not been discussed in the literature. Therefore, here we develop a cusum test for parameter change in a more general framework. As an example, we consider the change of the parameters in an RCA(1) model and that of the autocovariances of a linear process. We also consider the variance change test for unstable models with unit roots and GARCH models.

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Correction of Coordinate Discontinuities Caused by GPS Antenna Replacements

  • Kim, Dusik;Park, Kwan-Dong;Won, Jihye
    • Journal of Positioning, Navigation, and Timing
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    • 제4권3호
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    • pp.131-140
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    • 2015
  • Antennas at permanent GPS stations operated by the former Ministry of Government Administration and Home Affairs (MOGAHA) in Korea were replaced in years 2008 and 2009, and these changes caused abrupt discontinuities in precise coordinate time series. In this study, an algorithm that eliminates those breaks was developed based on 15-year-long coordinate time series for the purpose of creating clean and continuous coordinate time series. The newly developed algorithm to correct for sudden jumps and dips in the GPS time series due to the antenna change was designed to consider all the linear and annual signals observed before and after the event. The accuracy of the new algorithm was confirmed to be at the Root Mean Square Error (RMSE) level of 2.3-2.6 mm. The new algorithm was also found to be capable of reflect site-specific characteristics at each station.

COVID-19 사례를 통한 도시 내 비정상적 수요 예측을 위한 시계열 모형 파이프라인 개발 연구 (Time Series Modeling Pipeline for Urban Behavioral Demand Prediction under Uncertainty)

  • 진민수;이동우;김영록;이현수
    • 한국ITS학회 논문지
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    • 제22권2호
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    • pp.80-92
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    • 2023
  • 도시에 많은 사람들이 밀집하여 살아가면서 기존에 예측하지 못했던 범죄, 사고, 감염병 등의 비정상 이벤트가 발생은 도시 내 이용자 수요에 영향을 미치게 된다. 이러한 불확실성(uncertainty)이 내포된 정보를 기반으로 도시 내 이용자 수요에 대한 시계열적 예측을 수행한다면 신뢰성 있는 결과 도출이 불가능하다. 특히, 2020년 초 발발한 COVID-19는 비정상적인 이동통행패턴의 변화를 불러 일으키며 시계열 수요예측을 어렵게 만들었기에 이러한 변화를 검지하고 이를 반영하여 정확한 수요를 예측 수행할 수 있는 방법론의 필요성이 대두되고 있다. 이에 본 연구는 COVID-19로 인한 비정상적 이벤트를 자동으로 검지하고 예측하는 모형 파이프라인을 구축하였다. 이는 도시 내 다양한 분야에서의 불규칙적이고 비정상적인 이벤트로 인한 수요변화가 일어나는 상황에 폭넓게 활용될 수 있을 것으로 생각된다.

Damage detection of railway bridges using operational vibration data: theory and experimental verifications

  • Azim, Md Riasat;Zhang, Haiyang;Gul, Mustafa
    • Structural Monitoring and Maintenance
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    • 제7권2호
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    • pp.149-166
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    • 2020
  • This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

LSTM-based Sales Forecasting Model

  • Hong, Jun-Ki
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권4호
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    • pp.1232-1245
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    • 2021
  • In this study, prediction of product sales as they relate to changes in temperature is proposed. This model uses long short-term memory (LSTM), which has shown excellent performance for time series predictions. For verification of the proposed sales prediction model, the sales of short pants, flip-flop sandals, and winter outerwear are predicted based on changes in temperature and time series sales data for clothing products collected from 2015 to 2019 (a total of 1,865 days). The sales predictions using the proposed model show increases in the sale of shorts and flip-flops as the temperature rises (a pattern similar to actual sales), while the sale of winter outerwear increases as the temperature decreases.

시계열로 분석한 한국사회의 사회안전지표 (Safety Index of Korean Society Analyzed by Time Series)

  • 신창섭;김성민;황석근;이경덕;이재열
    • 한국안전학회지
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    • 제21권6호
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    • pp.55-63
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    • 2006
  • Rapid economic growth in Korea, on the other side, has generated increase of multiple complex dangers. To take off dangers scattered in the Korean society and to conduct safe society for better life, it is needed to develop social safety index. Social safety index analyzed by time series could compare and estimate various social disasters, thus it act as the foundation to set up safety policy. The research has focused on 8 social safety indexes; natural disaster, fire, traffic accident, crime, industry accident, forest fire, collapse and explosion, and environmental pollution. To find out Korean society safety index analyzed by time series, the research analyzed changes of each safety indexes in 10 years since 1994. Looking at the changes of each indexes, traffic accident showed the most improvement overall the nation, with industrial accident and collapse and explosion rating second and third place. However, crime, fire and natural disaster get worse, and especially crime has turned worsened than any other divisions.