Modified Kernel Marginal Fisher Analysis for Feature Extraction and Its Application to Bearing Fault Diagnosis by Li Jiang, Shunsheng Guo

“…It firstly utilizes MKMFA to directly extract the low-dimensional manifold characteristics from the raw time-series signal samples in high-dimensional ambient space. …”
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BILATERAL J-CURVE BETWEEN TURKEY AND THE EUROZONE by Furkan Emirmahmutoglu, Mert Topcu, Salih Özdemir

“…In the case of Turkey where foreign trade volume is largely dominated by the Eurozone countries, one set of studies examines the J-curve phenomenon using total trade data while a second set of studies investigates the validity of the bilateral J-curve within a time-series framework. This study intends to investigate the validity of the bilateral J-curve between Turkey and the Eurozone over the period 2002:Q1-2019:Q4 within a dynamic panel data framework robust to heterogeneity and cross-section dependence. …”
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Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks in Nonlinear Identification by Oscar Castillo, Juan R. Castro, Patricia Melin, Antonio Rodriguez-Diaz

“…Simulation results of nonlinear function identification using the IT2FNN for one and three variables and for the Mackey-Glass chaotic time series prediction are presented to illustrate the concept of universal approximation.…”
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Short-Term Passenger Flow Prediction of Urban Rail Transit Based on SDS-SSA-LSTM by Haijun Li, Yongpeng Zhao, Changxi Ma, Ke Wang, Xiaoting Huang, Wentao Zhang

“…Then, based on this strategy, the passenger flow time series with complex features is decomposed into a relatively single trend and fluctuation component. …”
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Markov Switching Model Analysis of Implied Volatility for Market Indexes with Applications to S&P 500 and DAX by Luca Di Persio, Samuele Vettori

“…We adopt a regime switching approach to study concrete financial time series with particular emphasis on their volatility characteristics considered in a space-time setting. …”
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Accurate identification of oxygen desaturation status in COPD by using classifier ensemble. by Yue-Fang Wu, Xin Shu, Shiqi Wang, Xiaojun Xu, Pei-Li Sun

“…In the proposed method, five different features of each data point from the time series of SpO2 and pulse are extracted and then combined to form the discriminative feature of the corresponding data point; then, multiple base classifiers with different balanced training subsets are trained and then integrated by using AdaBoost Algorithm. …”
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Tourism Demand Forecasting Based on Grey Model and BP Neural Network by Xing Ma

“…The prediction accuracy of the model is analyzed by the actual time series data of the number of tourists. Finally, the experimental analysis shows that the combination forecasting makes full use of the information provided by each forecasting model and obtains the combination forecasting model and the best forecasting result so as to improve the forecasting accuracy and reliability.…”
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Development and application of machine learning models in US consumer price index forecasting: Analysis of a hybrid approach by Yunus Emre Gur

“…The study examined the performance of LSTM, MARS, XGBoost, LSTM-MARS, and LSTM-XGBoost models using a large time-series data from January 1974 to October 2023. …”
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Stayed-Cable Bridge Damage Detection and Localization Based on Accelerometer Health Monitoring Measurements by Mosbeh R. Kaloop, Jong Wan Hu

“…The statistical and model identification time series, the response spectra, and the power density of the frequency domain are used to detect the behavior of Yonghe cable-stayed bridge during the healthy and damage states. …”
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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

“…However, when considering the overall trend, there was an upward trend with a slope of 3.53× -2. 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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A Causal and Correlation Analysis between China Energy Futures and China Energy-Related Companies Stock Market by Yufang Liu, Chi Zhang, Wang Zhang

“…Research shows that INE does have a causal relationship with the stock market of the related industry chain, and there is a multifractal correlation between its transaction time series. Subsequently, the source of fractal correlation was analysed with shuffled and surrogated sequences. …”
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The Multivariate Fusion Distribution Characteristics in Physician Demand Prediction by Jiazhen Zhang, Wei Chen, Xiulai Wang

“…Aiming at the optimization of the big data infrastructure in China’s healthcare system, this study proposes a lightweight time series physician demand prediction model, which is especially suitable for the field of telemedicine. …”
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A large synthetic dataset for machine learning applications in power transmission grids by Marc Gillioz, Guillaume Dubuis, Philippe Jacquod

“…The method allows one to generate arbitrarily large time series from the knowledge of the grid – the admittance of its lines as well as the location, type and capacity of its power generators – and aggregated power consumption data, such as the national load data given by ENTSO-E. …”
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Event-Triggered-Based External Consensus Protocol of RBF-ARX-Model-Based Networked Multiagent Systems with Nonlinear Dynamics and Communication Delays by Qi Lei, Ying Luo

“…By utilizing the RBF-ARX model, the locally linearized time series model can be obtained to describe the behaviour of agents with nonlinear characteristics. …”
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Analysis of the influence internal and external factors on the performance of IDXV30 by Tumpal Samosir, Pardomuan Sihombing

“…Type of data used is monthly time series data using the saturated sampling technique which is processed using the Eviews 12 application program using the VECM analysis method. …”
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From threat to response: Cybersecurity evolution in Albania by Klorenta PASHAJ, Vilma TOMÇO, Eralda GJIKA

“…One key recommendation is the forecasting of cyber-attacks, which could benefit from the application of time-series and machine learning techniques to enhance predictive capabilities. …”
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Rational emotive behavioral education model to reduce aggressive behavior in adolescents by Isti Widya Khairunnisa, Feida Noor Laila Isti'adah, Gian Sugiana Sugara

“…The experimental study with Time Series Design was conducted for 5 weeks, with one REBE intervention session per week for 40-60 minutes. …”
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Global Tomato Production: Price Sensitivity and Policy Impact in Mexico, Türkiye, and the United States by Ramu Govindasamy, Rahmiye Figen Ceylan, Burhan Özkan

“…This study analyzed the impact of price fluctuations and evolving agricultural support schemes on tomato production in three key producers: Mexico, Türkiye, and the United States, which play significant roles in the global market with specialized production and trade. Using time-series price response data from 1991 to 2022, the research examined market prices, government support policies, and international trade agreements. …”
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Differences in Energy Consumption in Electric Vehicles: An Exploratory Real-World Study in Beijing by Kezhen Hu, Jianping Wu, Tim Schwanen

“…The proposed method for analyzing time series data about energy consumption along routes can be used for research with larger fleets of EVs in the future.…”
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Post-processing methods for delay embedding and feature scaling of reservoir computers by Jonnel Jaurigue, Joshua Robertson, Antonio Hurtado, Lina Jaurigue, Kathy Lüdge

“…Abstract Reservoir computing is a machine learning method that is well-suited for complex time series prediction tasks. Both delay embedding and the projection of input data into a higher-dimensional space play important roles in enabling accurate predictions. …”
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