An empirical investigation of the underlying factors of recently declining air pollution in China by Emrah Eray Akça, Tayfun Tuncay Tosun

“…This study analyses the underlying factors of recently declining air pollution in China, utilizing annual time series data from 2000 to 2020 in the autoregressive distributed lag model approach framework. …”
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Research on the Impact of Sino-US Trade Structure on the Real Effective Exchange Rate of RMB by Jiajia Yan, Jinlong Cai

“…In order to analyze the impact of Sino-US trade on the RMB exchange rate, based on the Sino-US import and export trade data under the quarterly HS classification from 2003 to 2019 and the RMB real effective exchange rate, this article carries out the traditional time series test, seasonal unit root test, and cointegration test and further constructs the seasonal error correction model to explore the long-term and short-term dynamic impact of Sino-US import and export trade structure on RMB real effective exchange rate. …”
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Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm by Baraa Yousif Salman, Jaber Parchami

“…Regression functions and machine learning algorithms have a very good performance in predicting time series data. In this research, the optimized support vector regression (SVR) algorithm has been used to improve the accuracy of air delay prediction. …”
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Exergetic Assessment for Resources Input and Environmental Emissions by Chinese Industry during 1997–2006 by Bo Zhang, Beihua Peng, Mingchu Liu

“…Exergy intensities in terms of resource input intensity and environmental emission intensity time-series are also calculated, and the trends are influenced by the macroeconomic situation evidently, particularly by the investment-derived economic development in recent years. …”
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Dynamic Analysis and Circuit Realization of a Novel No-Equilibrium 5D Memristive Hyperchaotic System with Hidden Extreme Multistability by Qiuzhen Wan, Zhaoteng Zhou, Wenkui Ji, Chunhua Wang, Fei Yu

“…The system parameters-dependent and memristor initial conditions-dependent dynamical characteristics of the proposed memristive hyperchaotic system are investigated in terms of phase portrait, Lyapunov exponent spectrum, bifurcation diagram, Poincaré map, and time series. Then, the hidden dynamic attractors such as periodic, quasiperiodic, chaotic, and hyperchaotic attractors are found under the variation of its system parameters. …”
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Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network-Based Marine Predators Algorithm by Sarah J. Mohammed, Salah L. Zubaidi, Nadhir Al-Ansari, Hussein Mohammed Ridha, Nabeel Saleem Saad Al-Bdairi

“…The finding demonstrated that singular spectrum analysis is a highly effective method to denoise time series. MPA-ANN outperformed CPSOCGSA-ANN and SMA-ANN algorithms based on different statistical criteria. …”
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Understanding tinnitus symptom dynamics and clinical improvement through intensive longitudinal data by Milena Engelke, Jorge Piano Simões, Laura Basso, Nina Wunder, Berthold Langguth, Thomas Probst, Rüdiger Pryss, Winfried Schlee

“…App data from a multi-center randomized clinical trial were analysed using time-series feature extraction and nested cross-validated ordinal regression with elastic net regulation to predict clinical improvement based on the Clinical Global Impression—Improvement scale (CGI-I). …”
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Rapid Progression of Heterotopic Ossification in Severe Variant of Fibrodysplasia Ossificans Progressiva with p.Arg258Gly in ACVR1: A Case Report and Review of Clinical Phenotypes by Kosei Hasegawa, Hiroyuki Tanaka, Natsuko Futagawa, Hiroyuki Miyahara, Hirokazu Tsukahara

“…Heterotopic ossification occurred earlier and more frequently compared with classical FOP patients. We present the time-series changes in heterotopic ossification in our patient and compare her clinical features with those of the previously reported patients with p.Arg258Gly. …”
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Analyses of the Spatial Pattern of Drought Risk in Tigray Region, Northern Ethiopia by A.S. Tefera, J.O. Ayoade, N.J. Bello

“…Monthly Gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.01 data on twelve selected stations, was used to calculate the Standard Precipitation and Evapotranspiration Index (SPEI). …”
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FEDERAL GOVERNMENT AGRICULTURAL FINANCING AND ECONOMIC GROWTH IN NIGERIA by Rasaki Olufemi Kareem, Rukayat Adebunmi Arije, Zakariah Olayiwola Amoo, Hassan Yusuf Avovome

“…The study utilized the time series data which was extracted from the Central Bank of Nigeria statistical bulletin. …”
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Potential of Adding Constructed Wetland/Fishpond to Waste Stabilization Ponds to Improve Helminths Removal in Morogoro Municipality, Tanzania by A.H. Outwater, A. Zachariah, A. Nyomora, F. Francis, J.H.Y. Katima

“…Water, soil, and vegetable samples were tested for the presence of helminth larvae and eggs in a time series design over one growing season. From March to August 2014, experimental plots of carrots and Swiss chard were irrigated with wastewater that had been treated by the alternative wastewater treatment regime. …”
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Lunar Calendar Usage to Improve Forecasting Accuracy Rainfall via Machine Learning Methods by Gumgum Darmawan, Gatot Riwi Setyanto, Defi Yusti Faidah, Budhi Handoko

“…The lunar calendar is often overlooked in time-series data modeling despite its importance in understanding seasonal patterns, as well as economics, natural phenomena, and consumer behavior. …”
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Estimating Alarm Thresholds for Process Monitoring Data under Different Assumptions about the Data Generating Mechanism by Tom Burr, Michael S. Hamada, John Howell, Misha Skurikhin, Larry Ticknor, Brian Weaver

“…The second example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals.…”
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Daily Prediction Model of Photovoltaic Power Generation Using a Hybrid Architecture of Recurrent Neural Networks and Shallow Neural Networks by Wilson Castillo-Rojas, Juan Bekios-Calfa, César Hernández

“…RNN models have a particular configuration that makes them efficient for processing ordered data in time series. The results of this work have been obtained through controlled experiments with different configurations of its hyperparameters for hybrid RNN-ANN models. …”
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Hybridized Extreme Learning Machine Model with Salp Swarm Algorithm: A Novel Predictive Model for Hydrological Application by Zaher Mundher Yaseen, Hossam Faris, Nadhir Al-Ansari

“…Twenty years of river flow data time series of the Tigris river at the Baghdad station, Iraq, is used as a case study. …”
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Applying Fourier Neural Operator to insect wingbeat sound classification: Introducing CF-ResNet-1D by Béla J. Szekeres, Máté Natabara Gyöngyössy, János Botzheim

“…Despite recent advancements in Deep Learning, Fourier Neural Operators (FNO), efficient for solving Partial Differential Equations due to their global spectral representations, have yet to be thoroughly explored for real-world time series classification or regression tasks. This study explores the application of FNOs in insect wingbeat sound classification, focusing on their potential for improving the accuracy and efficiency of such tasks, particularly in the fight against mosquito-borne diseases. …”
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Recurrent Patterns of User Behavior in Different Electoral Campaigns: A Twitter Analysis of the Spanish General Elections of 2015 and 2016 by S. Martin-Gutierrez, J. C. Losada, R. M. Benito

“…By computing and analyzing the time series of daily activity, we have found a significant linear correlation between both elections. …”
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A Photovoltaic Array Fault Diagnosis Method Considering the Photovoltaic Output Deviation Characteristics by Jian Zhao, Qian Sun, Ning Zhou, Hao Liu, Haizheng Wang

“…Based on the current of the PV array on the DC (direct current) side, the deviation characteristics of the PV array output under different arrays and time series are analyzed. Then, the deviation function is constructed to evaluate the output deviation of the PV array. …”
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Forecasting the number of rural migrant workers in Chongqing using the optimized grey N_Verhulst model by Dai Liu, Chengxiang He, Jianlong Ma

“…It expands from 1 to all real numbers, thus enhancing its capacity to mine approximately saturated S-shaped time-series data. When the new N_Verhulst model is applied to simulate and predict migrant worker numbers, after optimizing the accumulating order, the mean relative simulation percentage error of the N_Verhulst model reduces from 3.66 to 2.93%, the mean relative forecasting percentage error from 8.02 to 2.18%, and the comprehensive mean relative percentage error from 4.53 to 2.78%. …”
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New Methods in Exploring Old Topics: Case Studying Brittle Diabetes in the Family Context by Moritz Philipp Günther, Peter Winker, Stefan A. Wudy, Burkhard Brosig

“…In questing for a more refined quantitative research approach, we revisited vector autoregressive (VAR) modeling for the analysis of time series data in the context of the so far poorly explored concept of family dynamics surrounding instable diabetes type 1 (or brittle diabetes). …”
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