Enhancing Smart Grids for Sustainable Energy Transition and Emission Reduction with Advanced Forecasting Techniques by Farah Rania, Farou Brahim, Kouahla Zineddine and Seridi Hamid

“…Results show that the proposed approach successfully handles time series data to detect future CO2 emissions excess and outperforms state-of-the-art techniques.…”
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Estimating Climate Trends: Application to United States Plant Hardiness Zones by Nir Y. Krakauer

“…I outline a multistep methodology involving imputation of missing station values, geostatistical interpolation, and time series smoothing to update a climate variable’s expected value compared to a climatology period and apply it to estimating annual minimum temperature change over the coterminous United States. …”
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Harmonic Impact of Plug-In Hybrid Electric Vehicle on Electric Distribution System by A. Aljanad, Azah Mohamed

“…The PHEV is modeled as a current harmonic source by using the Open-Source Distribution System Simulator (OpenDSS) and DSSimpc software. Time series harmonic simulation was conducted to investigate the harmonic impact of PHEV on the system by using harmonic data obtained from a real electric vehicle. …”
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Temperature Variability over the Po Valley, Italy, according to Radiosounding Data by Boyan Hristozov Petkov

“…Two datasets, considered to describe intra- and interannual oscillations, respectively, were extracted from the measurements data and the results show that both types of fluctuations can be projected onto four empirical orthogonal functions (EOFs), interpreted as vertical distributions of oscillation amplitudes and four uncorrelated time series that represent the evolution of corresponding EOFs. …”
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Real-time event detection using recurrent neural network in social sensors by Van Quan Nguyen, Tien Nguyen Anh, Hyung-Jeong Yang

“…Second, an event detection model using a recurrent neural network is employed to learn time series data features by extracting temporal information. …”
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Non-traditional data to inform modern climate science by Kimberley R. Miner, Ethan Wong, Bradley A. Gay, Charles E. Miller

“…Even though the modern instrument-based record of Earth observations reflects decades of critical work, multi-century time series may be required to understand and forecast key elements of Earth system dynamics. …”
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An Analysis of the Economic Impact of US Presidential Elections Based on Principal Component and Logical Regression by Jing-Jing Wang, Yan Liang, Jin-Tao Su, Jia-Ming Zhu

“…At the same time, the future economic development of the United States and China based on the time series prediction model is forecast and analyzed, respectively. …”
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AN ANALYSIS OF THE DYNAMICS OF INVESTMENT SAVING AND ECONOMIC GROWTH IN TURKEY: 1950-2004 by Ercan Sarıdoğan, Sefer Şener, Deniz Şükrüoğlu

“…The methodology we applied depends on the time series econometric techniques which include analyzing the stationarity of the variables, cointegration, vector error correction mechanism, and Granger causality and vector auto regressive models with impulse-response and variance decomposition techniques. …”
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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. …”
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Modeling and Prediction of Momentum Wheel Speed Data by Jichao Li, Xiaxia Wang, Chaobo Chen, Song Gao

“…The long data sequence is converted into multidimensional time series, based on the equal interval data and the period. …”
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The Effect of the Financial Crisis on Investment Projects Case Study: Kurdistan Region of Iraq by Amanj Jalal Faiq

“…To accomplish this objective the statistical technique and economic analysis was applied for annual time series data from 2006 to 2017 by applying the compound annual growth rate Gordon growth model (CAGR). …”
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DEATHS FROM SUICIDE IN FINLAND FROM 2016 TO 2023 by TIMO PARTONEN, AKI EKLIN, MARJUT GRAINGER

“…ABSTRACT Objectives: Suicides have been recorded in Finland since 1751, which forms the longest uninterrupted time series on this topic in the world. Suicide mortality has been decreasing in Finland since 1990. …”
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Online Bayesian Data Fusion in Environment Monitoring Sensor Networks by Yang Dingcheng, Wang Zhenghai, Xiao Lin, Zhang Tiankui

“…We briefly review the errors on the data transfer channel between the sensor quantifying the physical phenomenon and the fusion node, and a discrete K -ary input and K -ary output channel is presented to model the data transfer channel, where K is the number of quantification levels at the sensor. Then, discrete time series models are used to estimate the mean value of the physical phenomenon, and the estimation error is modeled as a Gaussian process. …”
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A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP by Wen-Ze Wu, Tao Zhang, Chengli Zheng

“…The nonlinear grey Bernoulli model, abbreviated as NGBM(1,1), has been successfully applied to control, prediction, and decision-making fields, especially in the prediction of nonlinear small sample time series. However, there are still some problems in improving the prediction accuracy of NGBM(1,1). …”
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Machine Learning with Variable Sampling Rate for Traffic Prediction in 6G MEC IoT by Rongqun Peng, Xiuhua Fu, Tian Ding

“…We first investigate a VSR-NLMS adaptive prediction method to perform time series prediction dataset transformation. Then, we propose a VSR-LSTM algorithm for real-time prediction of network traffic. …”
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An Intercomparison between ERA-Interim Reanalysis and Observed Precipitation in Northeast China by Jie Zhou, Junhu Zhao

“…In terms of temporal characteristics, the time series of the ERA-Interim precipitation matches well with the observed precipitation in whole. …”
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Hybrid Deep Learning for Gas Price Prediction Using Multi-Factor and Temporal Features by Shuliang Zhang, Hao Wu, Jin Wang, Longsheng Du

“…In this paper, we innovatively apply k-means clustering to analyze the correlations of multiple factors affecting natural gas prices and design a hybrid deep learning model that integrates both multi-factor and time series features. Through experimental validation on three public datasets, our proposed model achieves industry-leading predictive performance with a mean squared absolute error of 2.27, which is approximately a 1/3 improvement over the current state-of-the-art methods.…”
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An Improved Grey Model with Time Power and Its Application by Jianming Jiang, Caixia Liu, Yuanguo Yao, Yumu Lu, Wanli Xie, Chong Liu

“…The grey system model with time power, which is often called the GM(1,1, tα), appeals considerable interest of research due to its effectiveness in time series forecasting. Aimed to improve further the GM(1,1, tα) model, this paper introduces a new whitening equation with variable coefficient into the original whitening equation which extends applicable scope; as a result, an improved grey model with time power, namely, OGM(1,1, tα), is proposed. …”
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Environmental degradation and food security in Somalia by Bile Abdisalan Nor, Yusniliyana Yusof

“…The autoregressive distributed lag (ARDL) model was utilized with annual time-series data from 1990 to 2019. The empirical results show significant negative impacts of environmental degradation and gross domestic product (GDP) on food security, persisting in the short and long terms. …”
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An Improved ARIMA-Based Traffic Anomaly Detection Algorithm for Wireless Sensor Networks by Qin Yu, Lyu Jibin, Lirui Jiang

“…Specifically, we improve the traditional time series ARIMA model to make traffic prediction and judge the traffic anomaly in a WSN. …”
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