Spatiotemporal Characteristics and Influential Factors of Electronic Cigarette Web-Based Attention in Mainland China: Time Series Observational Study by Zhongmin Zhang, Hengyi Xu, Jing Pan, Fujian Song, Ting Chen

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Multi-Step-Ahead Prediction of Chaotic Time Series: Self-Healing Algorithm for Restoring Values at Non-Predictable Points by Vasilii A. Gromov, Korney K. Tomashchuk, Alexey Rukavishnikov A.

“… Problem: The study proposes a new algorithm for multi-step-ahead prediction of chaotic time series within the framework of the clustering-based forecasting paradigm. …”
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Trend Analysis Method on Vertical Axis by Yavuz Selim GÜÇLÜ

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Forecasting basal area increment in forest ecosystems using deep learning: A multi-species analysis in the Himalayas by P. Casas-Gómez, J.F. Torres, J.C. Linares, A. Troncoso, F. Martínez-Álvarez

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Crypto Currency Price Forecast: Neural Network Perspectives by Yuriy Kleban, Tetiana Stasiuk

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Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling by Patricia Virginia de Santana Lima, David Venâncio da Cruz, Albaro Ramon Paiva Sanz

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Planetary Mass Determinations from a Simplified Photodynamical Model—Application to the Complete Kepler Dataset by Aviv Ofir, Gideon Yoffe, Oded Aharonson

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Fine-scale satellite-based monitoring of temperature and vegetation cover in microclimates, distribution ranges, and landscape connectivity for Neurergus kaiseri (Kaiser’s mountain... by Peyman Karami, Sajad Tavakoli, Mina Esmaeili

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Application of a generalized additive mixed model in time series study of dairy cow behavior under hot summer conditions by C. Ferrari, C. Evangelista, L. Basiricò, S. Castellani, S. Biffani, U. Bernabucci

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Insights into mapping tropical primary wet forests in the Amazon Basin from satellite-based time series metrics of canopy stability by Brendan Mackey, Sonia Hugh, Tatiana Shestakova, Brendan M. Rogers, Ludmila Rattis

“…Canopy stability was explored using a time series of remotely sensed MODIS data for the period 2003–2019 at a 500 m pixel resolution. …”
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Tropical Rice Mapping Using Time-Series SAR Images and ESF-Seg Model in Hainan, China, from 2019 to 2023 by Yazhe Xie, Lu Xu, Hong Zhang, Mingyang Song, Ji Ge, Fan Wu

“…To address this difficulty, a new deep learning model, ESF-Seg, is proposed in this study to extract the annual tropical rice distribution using monthly averaged time-series Sentinel-1 VH data. The ESF-Seg adopts the Efficient Adaptive Sparse Transformer (EAT) to remove redundant information from input features. …”
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Fusing MODIS and AVHRR products to generate a global 1-km continuous NDVI time series covering four decades by Xiaobin Guan, Huanfeng Shen, Yuchen Wang, Dong Chu, Xinghua Li, Linwei Yue, Wei Li, Xinxin Liu, Liangpei Zhang

“…Satellite normalized difference vegetation index (NDVI) time series, essential for ecological and environmental applications, is still limited by a trade-off between the spatiotemporal resolution and time coverage despite various global products. …”
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Metatranscriptomic time series insight into antibiotic resistance genes and mobile genetic elements in wastewater systems under antibiotic selective pressure by An-Dong Li, Yuanfang Chen, Lei Han, Ye Li, Ming Xu, Baoli Zhu

“…Metatranscriptomic data from the samples in the reactors were detected in a time series (0 to 10 h). The transcription profiles of ARGs and MGEs were summarized by searching metatranscriptomic datasets against related databases. …”
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Research on the Correlation between Information and Communication Technology Development and Consumer Spending Based on Artificial Intelligence and Time Series Econometric Model by Chaozhi Fan, Siong Hook Law, Saifuzzaman Ibrahim, N. A. M. Naseem

“…In order to explore the correlation between ICT development and consumer spending, this paper uses artificial intelligence and time series econometric models to study the correlation between ICT development and consumer spending. …”
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Species-Level Saltmarsh Vegetation Fractional Cover Estimation Based on Time Series Sentinel-2 Imagery with the Assistance of Sample Expansion by Jinghan Sha, Zhaojun Zhuo, Qingqing Zhou, Yinghai Ke, Mengyao Zhang, Jinyuan Li, Yukui Min

“…We chose the Yellow River Delta as the study area and utilized the time series Sentinel-2 imagery and random forest regression model for species-level FVC estimation with the assistance of FVC-WGAN-generated samples. …”
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Interrupted time series analysis to evaluate the impact of COVID-19-pandemic on the incidence of notifiable infectious diseases in the Lazio region, Italy by Martina Spaziante, Sara Leone, Maurizio D’Amato, Gabriella De Carli, Gilda Tonziello, Giorgio Nicolò Malatesta, Alessandro Agresta, Claudia De Santis, Valentina Vantaggio, Giovanni Pitti, Maria Concetta Fusco, Pierluca Piselli, Alessandra Barca, Enrico Girardi, Paola Scognamiglio, Francesco Vairo

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A Deep Learning-Based Approach for Two-Phase Flow Pattern Classification Using Void Fraction Time Series Analysis by Jefferson Dos Santos Ambrosio, Marco Jose da Silva, Andre Eugenio Lazzaretti

“…Codes are available at <uri>https://github.com/ambrosioj/two-phase-time-series-deep-learning</uri>.…”
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GeoTemporal clustering for aquifer delineation: a big data approach to synchronizing and analyzing variable-length groundwater time series by Khalid ElHaj, Dalal Alshamsi

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Correction: Hybrid GNSS time-series prediction method based on ensemble empirical mode decomposition with long short-term memory by Yu Zhou, Xiaoxing He, Shengdao Wang, Shunqiang Hu, Xiwen Sun, Jiahui Huang

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Impact of the COVID-19 pandemic on utilization of mental health services among children and adolescents using an interrupted time series analysis by Fumihiro Endo, Yuji Hiramatsu, Hiroo Ide

“…We conducted an interrupted time series analysis of the number of mental health visits and average incurred medical expenses, stratified by sex and age group, using monthly medical claims data on 3,029,048 patients for the period from January 2016 to December 2020. …”
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