Prediction of Epileptic Seizure by Analysing Time Series EEG Signal Using k-NN Classifier by Md. Kamrul Hasan, Md. Asif Ahamed, Mohiuddin Ahmad, M. A. Rashid

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LSTM-Based Time Series Prediction Model: A Case Study with YFinance Stock Data by Yu Yimiao

“…The goal of this study is to anticipate the time series of stock data that YFinance provides using a Long Short-Term Memory (LSTM) model, with a particular emphasis on the closing prices and daily returns of Apple Inc. …”
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Evaluation of Relations between Extreme Precipitation and Temperature in Observational Time Series from the Czech Republic by Marta Martinkova, Martin Hanel

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Precipitation, Time Series Models, Man-Kendall, Health Winters model, West Azerbaijan Province by Saeed jahanbakhshasl, ali mohammadkhorshiddoust, fatemeh abbsighasrik, zahra abbasighasrik

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Reliability Prediction of Ontology-Based Service Compositions Using Petri Net and Time Series Models by Jia Li, Yunni Xia, Xin Luo

“…In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. …”
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A Dynamic Interval Auto-Scaling Optimization Method Based on Informer Time Series Prediction by Yu Ding, Chenhao Li, Zhengong Cai, Xinghao Wang, Bowei Yang

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Time Series Analysis: Application of LSTM model in predicting PM 2.5 concentration in Beijing by Yang Rui

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Unfolding the Phase Space Structure of Noisy Time Series by means of Angular First-Return Maps by Javier Villa Briongos, Jesús Gómez-Hernández, Daniel Serrano, Domingo Santana

“…Finally, some experimental pressure time series measured on gas-solid fluidized beds operated at different dynamical regimes are presented to analyze the reliability of the proposed method to deal with experimental noise time series.…”
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A prediction approach to COVID-19 time series with LSTM integrated attention mechanism and transfer learning by Bin Hu, Yaohui Han, Wenhui Zhang, Qingyang Zhang, Wen Gu, Jun Bi, Bi Chen, Lishun Xiao

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Time Series Forecasting for Regional Development Composite Index Using Real-Time Floating Population Data by Jungyeol Hong, Jieun Na, Youjeong Kang, Dongho Kim

“…A correlation and cross-correlation analysis was performed to exhibit a clear relationship between composite development indices and floating population value. In addition, a time series model and a multiple regression model analyses were applied to predict regional development indices. …”
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The Utility of LiCSBAS to Carry out InSAR Time Series to Analyze Surface Deformation: An Overview by Zuhour Katia Thamer, Ahmed H. Hamdullah, Mamoun Ubaid Mohammed, Md Tanvir Sowgath

“…One such technique, LiCSBAS, has shown great promise in analyzing InSAR time series data to accurately detect and quantify surface displacements. …”
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Predictive Analysis of Economic Chaotic Time Series Based on Chaotic Genetics Combined with Fuzzy Decision Algorithm by Xiuge Tan

“…The irreversibility in time, the multicausality on lines, and the uncertainty of feedbacks make economic systems and the predictions of economic chaotic time series possess the characteristics of high dimensionalities, multiconstraints, and complex nonlinearities. …”
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Flexible Lévy-Based Models for Time Series of Count Data with Zero-Inflation, Overdispersion, and Heavy Tails by Confort Kollie, Philip Ngare, Bonface Malenje

“…The explosion of time series count data with diverse characteristics and features in recent years has led to a proliferation of new analysis models and methods. …”
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A Comparative Study of VMD-Based Hybrid Forecasting Model for Nonstationary Daily Streamflow Time Series by Hui Hu, Jianfeng Zhang, Tao Li

“…The latest decomposition model, the VMD algorithm, was first applied to extract the multiscale features from the entire time series and to decompose them into several subseries, which were predicted after that using forecast models. …”
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Mixing Data Cube Architecture and Geo-Object-Oriented Time Series Segmentation for Mapping Heterogeneous Landscapes by Michel E. D. Chaves, Lívia G. D. Soares, Gustavo H. V. Barros, Ana Letícia F. Pessoa, Ronaldo O. Elias, Ana Claudia Golzio, Katyanne V. Conceição, Flávio J. O. Morais

Subjects: “…satellite image time series…”
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Do changing medical admissions practices in the UK impact on who is admitted? An interrupted time series analysis by Jennifer Cleland, Amanda J Lee, Sandra Nicholson, Paul Alexander Tiffin, Rachel Greatrix, Shona Fielding, Fiona Patterson

“…However, evidence to what extent this shift in practice has actually widened access is conflicting.Aim To examine if changes in medical school selection processes significantly impact on the composition of the student population.Design and setting Observational study of medical students from 18 UK 5-year medical programmes who took the UK Clinical Aptitude Test from 2007 to 2014; detailed analysis on four schools.Primary outcome Proportion of admissions to medical school for four target groups (lower socioeconomic classes, non-selective schooling, non-white and male).Data analysis Interrupted time-series framework with segmented regression was used to identify the impact of changes in selection practices in relation to invitation to interview to medical school. …”
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Determination of the best time series model for forecasting annual rainfall of selected stations of Western Azerbaijan province by Somayeh Soltani gerdfaramarzi, Aref Saberi, Morteza Gheisouri

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Time-Series Load Online Prediction of Wind Turbine Based on Adaptive Multisource Operational Data Fusion by Ruojin Wang, Xiaodong Wang, Deyi Fu, Bin Yang, Yingming Liu

“…Random forest (RF) and WaveNet time series (WTS) are established as subinformation source models, and the influence of input features and historical data on load prediction is considered from horizontal and vertical dimensions. …”
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A Novel Damage Detection Algorithm using Time-Series Analysis-Based Blind Source Separation by A. Sadhu, B. Hazra

“…In the proposed method, BSS is first employed to estimate the modal response using the vibration measurements. Time-series analysis is then performed to characterize the mono-component modal responses and successively the resulting time-series models are utilized for one-step ahead prediction of the modal response. …”
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Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks by Narayanan Manikandan, Srinivasan Subha

“…Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. …”
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