Self-organized criticality and urban development by Michael Batty, Yichun Xie

“…We illustrate the theory using a unique space–time series of urban development for Buffalo, Western New York, which contains the locations of over one quarter of a million sites coded by their year of construction and dating back to 1773, some 60 years before the city began to develop. …”
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Quantifying urbanization-induced dynamics of urban sprawl using spatial metrics method in Adama City, Ethiopia by Shimelis Sishah Dagne, Hurgesa Hundera Hirpha, Addisu Teshome Tekoye, Zenebe Reta Roba, Mitiku Badasa Moisa

“…This study aims to quantify the urbanization-induced dynamics of urban sprawl using spatial metrics method in Adama City. Time series Landsat TM, ETM+, and OLI/TIRS datasets were utilized to prepare LULC maps of the study area for the years 1992, 2002, 2012, and 2022 using supervised classification technique. …”
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Research on the Spread Path and Evolution Causes of Oral Language in the Digital Era by Zhiqiang Li

“…Through experiments on chaotic time series data sets, we find that HD-MFEA neuro-evolution algorithm is far superior to other evolutionary algorithms, and its convergence speed and accuracy are better than the gradient algorithm commonly used in neural network training.…”
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Simulation of an intense tropical cyclone in the conformal cubic atmospheric model and its sensitivity to horizontal resolutionhttps://cds.climate.copernicus.eu/ by Son C. H. Truong, Hamish A. Ramsay, Tony Rafter, Marcus J. Thatcher

“…Both grid configurations show similar time series of maximum wind speed (Vmax) and minimum sea level pressure (SLPmin). …”
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Brain state forecasting for precise brain stimulation: Current approaches and future perspectives by Matteo De Matola, Carlo Miniussi

“…After reviewing the state of the art in brain state-dependent stimulation, we will discuss two broad classes of forecasting methods and their suitability for application to EEG time series. Subsequently, we will review the evidence in favour of data-driven forecasting and discuss its potential contributions to TMS methodology and the scientific understanding of brain dynamics, highlighting the transformative potential of big open datasets.…”
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Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…Using RSTL to differentiate between time series data into development, seasonal in nature, and residual factors, this methodology addresses SI’s unpredictable nature and intermittent operation and provides the basis for accurate predictions. …”
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An Automated Approach for Epilepsy Detection Based on Tunable Q-Wavelet and Firefly Feature Selection Algorithm by Ahmed I. Sharaf, Mohamed Abu El-Soud, Ibrahim M. El-Henawy

“…The first perspectives consider the EEG signal as a nonlinear time series. A tunable Q-wavelet is applied to decompose the signal into smaller segments called subbands. …”
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Spectroscopic aspects of underwater digital holography of plankton by Victor Dyomin, Igor Polovtsev, Alexandra Davydova, Nikolai Kirillov

“…One of them is the time series of the concentration of individuals of various plankton taxa in a certain volume. …”
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Topology Unveiled: A New Horizon for Economic and Financial Modeling by Yicheng Wei, Junzo Watada, Zijin Wang

“…Meanwhile, in contemporary economics, topology is being used for high-dimension reduction, complex network construction, and structural data mining, combined with techniques of machine learning, and applied to high-dimensional time series and structure analysis in financial markets. …”
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Terrain Adaptive Estimation of Instantaneous Centres of Rotation for Tracked Robots by Cuifeng Wang, Wenjun Lv, Xiaochuan Li, Mingliang Mei

“…The results of this terrain classification are improved via a Bayesian filter, by utilizing temporal correlation in the terrain time series. Third, the performances of the ICR estimation and terrain classification are mutually promoted. …”
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High Resolution of Water Availability for Emilia-Romagna Region over 1961–2015 by F. Cervi, M. M. Nistor

“…In this study, monthly time series of precipitations and temperatures from 1024 controlled and homogeneous meteorological stations located in the Emilia-Romagna region (northern Italy) are processed in order to assess potential climate changes that occurred during the period 1961–2015. …”
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QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

“…To address these challenges, we present QPPLab, an open-source MATLAB-based toolbox for detecting, analyzing, and visualizing QPPs from fMRI time series. QPPLab integrates correlation-based iterative algorithms, supports customizable parameter settings, and features automated workflows to simplify analysis. …”
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Space-based long term condition monitoring of cold region pavement with PS-InSAR by Yusheng Jiang, Xiong Yu

“…InSAR algorithm based on Persistent scatterers (PS-InSAR) were implemented for data analyses. Time series displacement across five distinct persistent scatterers (PSs) groups at different locations were obtained. …”
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A Dual-Channel and Frequency-Aware Approach for Lightweight Video Instance Segmentation by Mingzhu Liu, Wei Zhang, Haoran Wei

“…However, traditional video instance segmentation methods face complex models, high computational overheads, and slow segmentation speeds in time-series feature extraction, especially in resource-constrained environments. …”
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Fast Simulation and Chaos Investigation of a DC-DC Boost Inverter by Rachid Dhifaou, Houda Brahmi

“…The second goal is to use this result to develop a discrete iterative map formulated as in standard discrete time series models. The Jacobian matrix of the found iterative map is defined and used to compute Lyapunov exponents to prove existence of chaos. …”
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Educational Trajectories of Parents as a Factor of Reproductive Behavior on the Example of the Republic of Tatarstan (2013-2022) by Ch. I. Ildarhanova, G. N. Ershova

“…The main methods were a cross-sectional analysis of data from sociological studies on the generative behavior of men and women in the Republic of Tatarstan, a statistical analysis of time series of indicators of age and education of parents. …”
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Predviđanje razvoja povrtarstva u Republici Srpskoj (Forecasting of Vegetable Production in Republic of Srpska) by Beba Mutavdžic, Ljiljana Drinic, Nebojša Novković, Aleksandar Ostojić, Gordana Rokvic

“…The prediction is based on modern quantitative methods, specifically applied the method of time series analysis , and used the appropriate ARIMA models.The form choice of the model is the result of qualitative analysis and statistical criteria. …”
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Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence by Abhinandan Khan, Sudip Mandal, Rajat Kumar Pal, Goutam Saha

“…We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. …”
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Robust Prediction of Healthcare Inflation Rate With Statistical and AI Methods in Iran by Mohammad Javad Shaibani, Ali Akbar Fazaeli

“…In this context, a robust approximation of HCIR will be a helpful tool for health authorities and other decision makers. Using monthly time series data of HCIR in Iran, we developed various forecasting techniques based on classical smoothing methods, decomposition ETS (error, trend, and seasonality) approaches, autoregressive (AR) integrated moving average (ARIMA), seasonal ARIMA (SARIMA), and a multilayer nonlinear AR artificial neural network (NARANN) with several training algorithms including Bayesian regularization (BR), Levenberg–Marquardt (LM), scaled conjugate gradient (SCG), Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton, conjugate gradient with Powell–Beale restarts (CGB), conjugate gradient with Fletcher–Reeves updates (CGF), and resilient propagation (RPROP) algorithms. …”
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Impact of attention on rare events across industries in Indonesia by Dedi Hariyanto, Rayenda Khresna Brahmana, Wendy Wendy

“…The article focused on all publicly listed industries on the Indonesian Stock Exchange (IDX/BEI). Using time series regression data from 1997 to 2020, the article comprised 5,615 observations across nine sectors. …”
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