A Comparative Study between Time Series and Machine Learning Technique to Predict Dengue Fever in Dhaka City by Tanzina Akter, Md. Tanvirul Islam, Md. Farhad Hossain, Mohammad Safi Ullah

“…According to the findings of this research, neural networks outperform time series analysis when it comes to making predictions. …”
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An Improved Demand Forecasting Model Using Deep Learning Approach and Proposed Decision Integration Strategy for Supply Chain by Zeynep Hilal Kilimci, A. Okay Akyuz, Mitat Uysal, Selim Akyokus, M. Ozan Uysal, Berna Atak Bulbul, Mehmet Ali Ekmis

“…For this purpose, historical data can be analyzed to improve demand forecasting by using various methods like machine learning techniques, time series analysis, and deep learning models. In this work, an intelligent demand forecasting system is developed. …”
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Astronomical Chronology Framework of the Lingshui Formation (Oligocene) in the Northern South China Sea by Jianhao Liang, Yaning Wang, Shangfeng Zhang, Yubing Liang, Gaoyang Gong, Rui Han

“…The astronomical timescale framework for the Lingshui Formation was accurately constructed by integrating geophysical logging data and employing a multidisciplinary approach that includes time series analysis, cyclostratigraphy, astronomical dating, and Power Ratio Accumulation (PRA) methods. …”
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A New Method of Kronecker Product Decomposition by Yi Wu

“…Kronecker product decomposition is often applied in various fields such as particle physics, signal processing, image processing, semidefinite programming, quantum computing, and matrix time series analysis. In the paper, a new method of Kronecker product decomposition is proposed. …”
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Music Recommendation Algorithm Based on Multidimensional Time-Series Model Analysis by Juanjuan Shi

“…This paper proposes a personalized music recommendation method based on multidimensional time-series analysis, which can improve the effect of music recommendation by using user’s midterm behavior reasonably. …”
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A Large-Scale Agricultural Land Classification Method Based on Synergistic Integration of Time Series Red-Edge Vegetation Index and Phenological Features by Huansan Zhao, Chunyan Chang, Zhuoran Wang, Gengxing Zhao

“…Moving beyond conventional time series analysis, we innovatively amplified key temporal characteristics through newly designed spatial feature parameters (SFPs) and phenological feature parameters (PFPs). …”
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Understanding Human Papillomavirus Vaccination Hesitancy in Japan Using Social Media: Content Analysis by Junyu Liu, Qian Niu, Momoko Nagai-Tanima, Tomoki Aoyama

“…Natural language processing techniques and large language models (LLMs) were used for stance analysis of the collected data. Time series analysis and latent Dirichlet allocation topic modeling were used to identify shifts in public sentiment and topic trends over the decade. …”
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A Semiparametric Approach for Modeling Partially Linear Autoregressive Model with Skew Normal Innovations by Leila Sakhabakhsh, Rahman Farnoosh, Afshin Fallah, Mohammadhassan Behzadi

“…The nonlinear autoregressive models under normal innovations are commonly used for nonlinear time series analysis in various fields. However, using this class of models for modeling skewed data leads to unreliable results due to the disability of these models for modeling skewness. …”
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The Optimal Supply Decision Based on Dynamic Multiobjective Optimization and Prediction by Kejia He, Hongyu Cheng, Yuchen Zhou, Cuihua Xie

“…In contrast to traditional approaches that rely on expert opinions, the proposed approach in this study allows the time series analysis (ARIMA) to forecast the trend in manufacturers’ development during the execution of the plan. …”
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A comparative study of symbolic aggregate approximation and topological data analysis by Fredrik Hobbelhagen, Ioannis Diamantis

“…Specifically, we applied topological data analysis (TDA) to analyze stock time series data and compared the results with those obtained using an expanded form of a more classical time series analysis method, symbolic aggregate approximation (SAX). …”
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Analysis of Rattleback Chaotic Oscillations by Michael Hanias, Stavros G. Stavrinides, Santo Banerjee

“…The emerging chaotic behaviour in all three cases has been studied and evaluated by the related time-series analysis and the calculation of the strange attractors’ invariant parameters.…”
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Air quality investigation using functional data analysis methods by Akvilė Vitkauskaitė, Milda Salytė

“…The analysis employs data smoothing, principal component analysis (PCA), exploratory data analysis, hypothesis testing, and time series analysis to provide a thorough examination. Functional data analysis approaches were used to find the origins and effects of these air pollutants by revealing their data patterns. …”
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Datasets for quantifying association between short-term exposure to maximum temperature and heatstroke-related ambulance dispatches in Japan: A time-stratified case-crossover desig... by Keita Wagatsuma

“…This resource is intended to support researchers, educators, and students in leveraging time-series analysis for research and educational purposes.…”
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Spatio-temporal behavior of atmospheriC concentration of NO2 using OMI sensor and its effect on precipitation in Iran by abolhassan gheibi, ali soleymani, hossein malakooti

“…In contrast, the time series analysis of average annual precipitation in Iran demonstrated a declining trend with a slope of (-0.159 mm × ). …”
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PREDICTING USD/ TL EXCHANGE RATE IN TURKEY: THE LONG-SHORT TERM MEMORY APPROACH by Abdul-razak Bawa Yussif, Fatih Mangır, Zeynep Karaçor, Ayten Yağmur

“…This is as a result of the inherent noise and the volatile behavior in these series. Time series analysis models such as ARIMA have been used for this purpose. …”
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Is Chinaʼs Capital Liberalisation Policy Effective? by Lirong Wang, Jinnan Zhou, C. James Hueng

“…These allow us to investigate the effects of Chinaʼs capital controls and subsequent liberalisation policies, along with various global‐push and domestic‐pull factors, on its gross capital flows in a time series analysis. We collect various sources of information on Chinaʼs capital control policies from 2005 to 2022 and construct quarterly time series of Chinaʼs capital control indices for different types of gross flows. …”
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Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation by Huili Xue, Kun Lin, Yin Luo, Hongjun Liu

“…The fluctuating wind speed process is investigated by the autoregressive (AR) model method in time series analysis. The accuracy and feasibility of the inverse approach are numerically investigated by identifying the wind load on a twenty-story shear building structure. …”
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Carbon Dioxide Emission Measurement and Its Spatiotemporal Evolution of Tourism Industry in Heilongjiang Province, China by Zi Tang, Tianyue Huang

“…The empirical results are as follows. (1) From 2010 to 2019, carbon dioxide emissions from Heilongjiang Province’s tourism industry and its subsector increased steadily, of which the tourism industry accounted for a relatively large amount of carbon dioxide emissions in “Transport, Storage, and Post.” (2) Time series analysis reveals that the carbon dioxide emissions of tourism basically show an increasing trend and there are still multiple decoupling relationships with economic growth. …”
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Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania by Joseph Lwaho, Bahati Ilembo

“…Originality/value – The study used partially processed secondary data to fit for Time series analysis using ARIMA (1,1,1) and hence reliable and conclusive results.…”
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Quadratic Forms in Random Matrices with Applications in Spectrum Sensing by Daniel Gaetano Riviello, Giusi Alfano, Roberto Garello

“…Quadratic forms with random kernel matrices are ubiquitous in applications of multivariate statistics, ranging from signal processing to time series analysis, biomedical systems design, wireless communications performance analysis, and other fields. …”
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