Using Time Deformation to Filter Nonstationary Time Series with Multiple Time-Frequency Structures by Mengyuan Xu, Wayne A. Woodward, Henry L. Gray

“…For nonstationary time series consisting of multiple time-varying frequency (TVF) components where the frequency of components overlaps in time, classical linear filters fail to extract components. …”
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Correction: Time series models for prediction of leptospirosis in different climate zones in Sri Lanka. by PLOS ONE Staff

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Forecasting the Number of Visitors of the Museums and Ruins by Using Time Series Analysis: The Case of Turkey by Mustafa Agah Tekindal, Semanur Öztemiz

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Fisher Discriminant Analysis for Extracting Interpretable Phenological Information From Multivariate Time Series Data by Conor T. Doherty, Meagan S. Mauter

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An Approach to Refining MODIS LAI Data Using a Fitting Scale Factor Time Series by Junxian Tang, Peijuan Wang, Rui Feng, Yang Li, Qing Li

“…To further refine the accuracy of the remotely sensed LAI, 1-km resolution land use data were resampled to 500-m resolution, and the pixel purity of spring maize was calculated for each 5-km grid cell. The scale factor time series was fitted with and without consideration of pixel purity, and the accuracy of the adjusted LAI using these two methods was compared. …”
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A robust adaptive meta-sample generation method for few-shot time series prediction by Chao Zhang, Defu Jiang, Kanghui Jiang, Jialin Yang, Yan Han, Ling Zhu, Libo Tao

Subjects: “…Few-shot time series prediction…”
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Time Series Forecasting Using Holt-Winters Exponential Smoothing: Application to Abaca Fiber Data by Mary Pleños

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Time series predictions in unmonitored sites: a survey of machine learning techniques in water resources by Jared D. Willard, Charuleka Varadharajan, Xiaowei Jia, Vipin Kumar

“…Modern machine learning methods increasingly outperform their process-based and empirical model counterparts for hydrologic time series prediction with their ability to extract information from large, diverse data sets. …”
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Time-Series Analysis of Continuously Monitored Blood Glucose: The Impacts of Geographic and Daily Lifestyle Factors by Sean T. Doherty, Stephen P. Greaves

“…Standard linear regression and more disaggregated time-series analysis using autoregressive integrated moving average (ARIMA) are used to explore patient BG variation throughout the day and over space. …”
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Grain Consumption Forecasting: One Modified MLR Model Combined with Time Series Forecasting Theory by Chunhua Zhu, Jiaojiao Wang, Jiake Tian

“…In this paper, one modified MLR model combined with time series forecasting theory is presented and applied in grain consumption forecasting. …”
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Time series forecasting of Valley fever infection in Maricopa County, AZ using LSTMResearch in context by Xueting Jin, Fangwu Wei, Srinivasa Srivatsav Kandala, Tejas Umesh, Kayleigh Steele, John N. Galgiani, Manfred D. Laubichler

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Integrating Drone Truthing and Functional Classification of Remote Sensing Time Series for Supervised Vegetation Mapping by Giacomo Quattrini, Simone Pesaresi, Nicole Hofmann, Adriano Mancini, Simona Casavecchia

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Digital mapping of soil organic carbon in a plain area based on time-series features by Kun Yan, Decai Wang, Yongkang Feng, Siyu Hou, Yamei Zhang, Huimin Yang

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Time series forecasting of bed occupancy in mental health facilities in India using machine learning by G. Avinash, Hariom Pachori, Avinash Sharma, SukhDev Mishra

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Damage Identification in Large-Scale Structures Using Time Series Analysis and Improved Sparse Regularization by Huihui Chen, Xiaojing Yuan

“…Aiming at the existing obstacles, this study enables to propose a novel method based on time series analysis model and improved sparse regularization technique for damage identification of the large-scale structure. …”
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Time series analysis of dengue incidence in Bandung City, Indonesia using a ARIMA model by Agung Sutriyawan, Martini Martini, Dwi Sutiningsih, Farid Agushybana, Nur Endah Wahyuningsih, Victor Eneojo Adamu, Hairil Akbar, Matheus Aba

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A New Time-Invariant Fuzzy Time Series Forecasting Method Based on Genetic Algorithm by Erol Eğrioğlu

“…In recent years, many fuzzy time series methods have been proposed in the literature. …”
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A Study of an Anomaly Detection System for Small Hydropower Data considering Multivariate Time Series by Bo Yang, Zhongliang Lyu, Hua Wei

“…Therefore, this paper proposes a real-time data anomaly detection system for small hydropower clusters (RDADS-SHC) considering multiple time series. It addresses the difficulties of timely detection, alerting, and management of real-time data anomalies (errors, omissions, and so on) in existing small hydropower stations. …”
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Investigating the Efficacy of Topologically Derived Time Series for Flare Forecasting. I. Data Set Preparation by Thomas Williams, Christopher B. Prior, David MacTaggart

“…We find that a number of time series in this data set often exhibit extremal signals that occur 1–8 hr before a flare. …”
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The association between the health promotion levy and employment in South Africa: an interrupted time series analysis by Chengetai Dare, Micheal Kofi Boachie, Susan Goldstein, Evelyn Thsehla

“…Methods We employed single-group interrupted time series analyses using the Quarterly Labour Force Survey data from Statistics South Africa. …”
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