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Transformers in Time-Series Analysis: A Tutorial
Circuits, Systems, and Signal Processing, 2022 Transformer architectures have widespread applications, particularly in Natural Language Processing and Computer Vision. Recently, Transformers have been employed in various aspects of time-series analysis.
Sabeen Ahmed +5 more
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American Journal of Orthodontics and Dentofacial Orthopedics, 2022
This article describes a simple method of applying a time series analysis to sample data sets using a free and open statistical software program, Language R.Records of new patients who visited 2 different university-affiliated orthodontic departments in 2 different countries were collected.
Richard E. Donatelli +3 more
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This article describes a simple method of applying a time series analysis to sample data sets using a free and open statistical software program, Language R.Records of new patients who visited 2 different university-affiliated orthodontic departments in 2 different countries were collected.
Richard E. Donatelli +3 more
openaire +4 more sources
SSRN Electronic Journal, 2006 Any series of observations ordered along a single dimension, such as time, may be thought of as a time series. The emphasis in time series analysis is on studying the dependence among observations at different points in time. What distinguishes time series analysis from general multivariate analysis is precisely the temporal order imposed on the ...
Francis X. Diebold +2 more
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One Fits All: Power General Time Series Analysis by Pretrained LM
Neural Information Processing Systems, 2023Although we have witnessed great success of pre-trained models in natural language processing (NLP) and computer vision (CV), limited progress has been made for general time series analysis.
Tian Zhou +4 more
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Time Series Analysis: Forecasting and Control
Journal of the American Statistical Association, 1978G. Box, G. Jenkins, G. Reinsel, G. Ljung
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A Survey on Deep Learning based Time Series Analysis with Frequency Transformation
Knowledge Discovery and Data Mining, 2023Recently, frequency transformation (FT) has been increasingly incorporated into deep learning models to significantly enhance state-of-the-art accuracy and efficiency in time series analysis.
Kun Yi +5 more
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IEEE transactions on intelligent transportation systems (Print), 2021
The real-time performance and accuracy of traffic flow prediction directly affect the efficiency of traffic flow guidance systems, and traffic flow prediction is a hotspot in the field of intelligent transportation.
Changxi Ma, G. Dai, Jibiao Zhou
semanticscholar +1 more source
The real-time performance and accuracy of traffic flow prediction directly affect the efficiency of traffic flow guidance systems, and traffic flow prediction is a hotspot in the field of intelligent transportation.
Changxi Ma, G. Dai, Jibiao Zhou
semanticscholar +1 more source
Foundations of Time Series Analysis
2021For almost a century, classical statistical methods including exponential smoothing and autoregression integrated moving averages (ARIMA) have been predominant in the analysis of time series (TS) and in the pursuit of forecasting future events from historical data.
Jonas, Ort +5 more
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Robust Time Series Analysis and Applications: An Industrial Perspective
Knowledge Discovery and Data Mining, 2022Time series analysis is ubiquitous and important in various areas, such as Artificial Intelligence for IT Operations (AIOps) in cloud computing, AI-powered Business Intelligence (BI) in E-commerce, Artificial Intelligence of Things (AIoT), etc.
Qingsong Wen +3 more
semanticscholar +1 more source