• Title/Summary/Keyword: 시계열 비교분석

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Comparative Analysis of RNN Architectures and Activation Functions with Attention Mechanisms for Mars Weather Prediction

  • Jaehyeok Jo;Yunho Sin;Bo-Young Kim;Jihoon Moon
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.10
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    • pp.1-9
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    • 2024
  • In this paper, we propose a comparative analysis to evaluate the impact of activation functions and attention mechanisms on the performance of time-series models for Mars meteorological data. Mars meteorological data are nonlinear and irregular due to low atmospheric density, rapid temperature variations, and complex terrain. We use long short-term memory (LSTM), bidirectional LSTM (BiLSTM), gated recurrent unit (GRU), and bidirectional GRU (BiGRU) architectures to evaluate the effectiveness of different activation functions and attention mechanisms. The activation functions tested include rectified linear unit (ReLU), leaky ReLU, exponential linear unit (ELU), Gaussian error linear unit (GELU), Swish, and scaled ELU (SELU), and model performance was measured using mean absolute error (MAE) and root mean square error (RMSE) metrics. Our results show that the integration of attentional mechanisms improves both MAE and RMSE, with Swish and ReLU achieving the best performance for minimum temperature prediction. Conversely, GELU and ELU were less effective for pressure prediction. These results highlight the critical role of selecting appropriate activation functions and attention mechanisms in improving model accuracy for complex time-series forecasting.

Road Accident Trends Analysis with Time Series Models for Various Road Types (도로종류별 교통사고 추세분석 및 시제열 분석모형 개발)

  • Han, Sang-Jin;Kim, Kewn-Jung
    • International Journal of Highway Engineering
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    • v.9 no.3
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    • pp.1-12
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    • 2007
  • Roads in Korea can be classified into four types according to their responsible authorities. For example, Motorway is constructed, managed, and operated by the Korea Highway Corporation. Ministry of Construction and Transportation is in charge of National Highway, and Province Roads are run by each province government. Urban/county Roads are run by corresponding local government. This study analyses the trends of road accidents for each road type. For this purpose, the numbers of accidents, fatalities, and injuries are compared for each road type for last 15 years. The result shows that Urban/County Roads are the most dangerous, while Motorways are the safest, when we simply compare the numbers of accidents, fatalities, and injuries. However, when we compare these numbers by dividing by total road length, National Highway becomes the most dangerous while Province Roads becomes the safest. In the case of road accidents, fatalities, and injuries per vehicle km, which is known as the most objective comparison measure, it turns out that National Highway is the most dangerous roads again. This study also developed time series models to estimate trends of fatalities for each road type. These models will be useful when we set up or evaluate targets of national road safety.

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BDS Statistic: Applications to Hydrologic Data (BDS 통계: 수문자료에의 응용)

  • Kim, Hyeong-Su;Gang, Du-Seon;Kim, Jong-U;Kim, Jung-Hun
    • Journal of Korea Water Resources Association
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    • v.31 no.6
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    • pp.769-777
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    • 1998
  • In this study, various time series are analyzed to check nonlinearities of the data. The nonlinearity of a system can be investigated by testing the randomness of the time series data. To test the randomness, four nonparametric test statistics and a new test statistic, called the BDS statistic are used and the results and the results are compared. The Brock, Dechert, and Scheinkman (BDS) statistic is originated from the statistical properties of the correlation integral which is used for searching for chaos and has been shown very effective in distinguishing nonlinear structures in dynamic systems from random structures. As a result of application to linear and nonlinear models which are well known, the BDS statistic is found to be more effective than nonparametric test statistics in identifying nonlinear structure in the time series. Hydrologic time series data are fitted to ARMA type models and the statistics are applied to the residuals. The results show that the BDS statistic can distinguish chaotic nonlinearity from randomness and that the BDS statistic can also be used for verifying the validity of the fitted model.

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Development of Data Visualization Tools for Land-Based Fish Farm Big Data Analysis System (육상 양식장 빅데이터 분석 시스템 개발을 위한 데이터 시각화 도구 개발)

  • Seoung-Bin Ye;Jeong-Seon Park;Hyi-Thaek Ceong;Soon-Hee Han
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.4
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    • pp.763-770
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    • 2024
  • Currently, land-based fish farms utilizing seawater have introduced and are utilizing various equipment such as real-time water quality monitoring systems, facility automation systems, and automated dissolved oxygen supply devices. Furthermore, data collected from various equipment in these fish farms produce structured and unstructured big data related to water quality environment, facility operations, and workplace visual information. The big data generated in the operational environment of fish farms aims to improve operational and production efficiency through the development and application of various methods. This study aims to develop a system for effectively analyzing and visualizing big data produced from land-based fish farms. It proposes a data visualization process suitable for use in a fish farm big data analysis system, develops big data visualization tools, and compares the results. Additionally, it presents intuitive visualization models for exploring and comparing big data with time-series characteristics.

The Comparison of Imputation Methods in Time Series Data with Missing Values (시계열자료에서 결측치 추정방법의 비교)

  • Lee, Sung-Duck;Choi, Jae-Hyuk;Kim, Duck-Ki
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.723-730
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    • 2009
  • Missing values in time series can be treated as unknown parameters and estimated by maximum likelihood or as random variables and predicted by the expectation of the unknown values given the data. The purpose of this study is to impute missing values which are regarded as the maximum likelihood estimator and random variable in incomplete data and to compare with two methods using ARMA model. For illustration, the Mumps data reported from the national capital region monthly over the years 2001 ${\sim}$ 2006 are used, and results from two methods are compared with using SSF(Sum of square for forecasting error).

국채선물을 이용한 채권포트폴리오의 VECM과 VAR모형에 의한 헤지

  • Han, Seong-Yun;Im, Byeong-Jin;Won, Jong-Hyeon
    • The Korean Journal of Financial Studies
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    • v.8 no.1
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    • pp.231-252
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    • 2002
  • 2000년 7월부터 채권시가평가의 실행으로 채권운용자들도 채권포트폴리오의 위험을 채권선물을 이용하여 통제하거나 감소시키기 위해 헤지를 하여야 한다. 이때 헤지비율을 추정하는 방법으로는 전통적 회귀분석모형, 백터오차수정모형(Vector Error Correction Model : VECM)과 VAR모형(Vector AutoRegressive Model)이 있다. 전통적인 회귀분석모형에 의하여 추정된 헤지비율은 시계열자료의 불안정성(nonstationary) 등으로 인하여 잘못 추정될 가능성이 있어 면밀한 검토와 분석 후 사용하여야 한다. 시계열자료의 불안정성으로 말미암아 야기되는 문제점들을 개선할 수 있는 모형으로서 VECM과 VAR모형이 널리 이용되고 있다. 따라서 본 연구는 VECM과 VAR모형을 사용하여 추정된 헤지비율과 전통적 회귀분석모형을 사용하여 추정한 헤지비율을 비교하여 어떤 모형으로 추정한 헤지비율이 더 정확한지를 평가하는데 목적을 두고 있다. 즉, 본 연구는 KTB 현 선물의 헤징에 대한 연구로 2000년 1월 4일부터 2001년 7월 27일까지 385일간의 KTB 현 선물 자료와 불룸버그 국채지수를 대상으로 VECM 및 VAR모형과 전통적 회귀분석모형에 의한 헤지비율을 추정하고 각 모형의 설명력과 예측력을 비교하고자 한다. 이 연구의 실증분석 결과, KTB 현물가격과 KTB 선물가격간, 블룸버그 국채지수와 KTB 선물가격간에는 공적분 관계가 존재하며, VECM 및 VAR와 전통적 회귀분석모형을 이용하여 추정한 최적헤지비율의 크기는 대동소이(大同小異)하며, 전통적 회귀분석방법을 이용하는 것이 VECM과 VAR모형을 이용할 때 보다 설명력과 예측력이 우월한 것으로 나타났다.

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Air passenger demand forecasting for the Incheon airport using time series models (시계열 모형을 이용한 인천공항 이용객 수요 예측)

  • Lee, Jihoon;Han, Hyerim;Yoon, Sanghoo
    • Journal of Digital Convergence
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    • v.18 no.12
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    • pp.87-95
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    • 2020
  • The Incheon airport is a gateway to and from the Republic of Korea and has a great influence on the image of the country. Therefore, it is necessary to predict the number of airport passengers in the long term in order to maintain the quality of service at the airport. In this study, we compared the predictive performance of various time series models to predict the air passenger demand at Incheon Airport. From 2002 to 2019, passenger data include trend and seasonality. We considered the naive method, decomposition method, exponential smoothing method, SARIMA, PROPHET. In order to compare the capacity and number of passengers at Incheon Airport in the future, the short-term, mid-term, and long-term was forecasted by time series models. For the short-term forecast, the exponential smoothing model, which weighted the recent data, was excellent, and the number of annual users in 2020 will be about 73.5 million. For the medium-term forecast, the SARIMA model considering stationarity was excellent, and the annual number of air passengers in 2022 will be around 79.8 million. The PROPHET model was excellent for long-term prediction and the annual number of passengers is expected to be about 99.0 million in 2024.

The forecasting evaluation of the high-order mixed frequency time series model to the marine industry (고차원 혼합주기 시계열모형의 해운경기변동 예측력 검정)

  • KIM, Hyun-sok
    • The Journal of shipping and logistics
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    • v.35 no.1
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    • pp.93-109
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    • 2019
  • This study applied the statistically significant factors to the short-run model in the existing nonlinear long-run equilibrium relation analysis for the forecasting of maritime economy using the mixed cycle model. The most common univariate AR(1) model and out-of-sample forecasting are compared with the root mean squared forecasting error from the mixed-frequency model, and the prediction power of the mixed-frequency approach is confirmed to be better than the AR(1) model. The empirical results from the analysis suggest that the new approach of high-level mixed frequency model is a useful for forecasting marine industry. It is consistent that the inclusion of more information, such as higher frequency, in the analysis of long-run equilibrium framework is likely to improve the forecasting power of short-run models in multivariate time series analysis.

On the Estimation Techniques of Hurst exponent (허스트 지수 산정 방법에 대한 고찰)

  • Kim, Byung-Sik;Kim, Hung-Soo;Seoh, Byung-Ha
    • Journal of Korea Water Resources Association
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    • v.37 no.12
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    • pp.993-1007
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    • 2004
  • There are many different techniques for the estimation of the Hurst exponent. However, the techniques can produce different characteristics for the persistence of a time series each other. This study uses several techniques such as adjusted range, resealed range(RR) analysis, modified restated range(MRR) analysis, 1/f power spectral density analysis, Maximum Likelihood Estimation(MLE), detrended fluctuations analysis(DFA), and aggregated variance time(AVT)method for the Hurst exponent estimation. The generated time series from chaos and stochastic systems are analyzed for the comparative study of the techniques. Then this study discusses the advantages and disadvantages of the techniques and also the limitations of them.

Analysis for Performance Enhancement of TMA using Apodized Time Sequence (Apodized 시계열을 사용한 TMA의 성능 향상에 대한 분석)

  • Ho, Kwang-Chun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.4
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    • pp.105-109
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    • 2018
  • In this paper, the performance enhancement of a time-modulated array is described. The proposed time-modulated array is based on the topology of a conventional array but uses apodized discrete time switching, instead of phase shifters, to achieve beamforming functions with side-band suppression. Numerical simulations are carried out to examine the performance of this beamforming system based on apodized time sequence of 16 elements linear array. Numerical results reveal that the proposed method provides a more flexible and accurate way of producing desired beampatterns with low or ultralow side-lobe level (SLL) compared with the conventional methods.