Time Series Analysis and Forecasting

TopicLeading institutions, researchers & key papers

This cluster of papers focuses on the clustering, classification, and analysis of time series data. It covers various algorithms and techniques such as dynamic time warping, feature extraction, deep learning, symbolic representation, multivariate classification, similarity measures, dimensionality reduction, and pattern discovery.

Works

IDs:OpenAlex

How has Time Series Analysis and Forecasting's publication output changed over time?

ScholarIQpublication output · 2010–2024

Output grew0% over the shown period — from 1 works in 2010 to 1 in 2024.

2010201220142015201620172018201920212024

What are the most-cited papers on Time Series Analysis and Forecasting?

ScholarIQmost cited works

PhysioBank, PhysioToolkit, and PhysioNet

Ary L. Goldberger, Luı́s A. Nunes Amaral, Leon Glass, Jeffrey M. Hausdorff, Plamen Ch. Ivanov, Roger G. Mark, Joseph E. Mietus, G.B. Moody, Chung‐Kang Peng, H. Eugene Stanley

Circulation. 200014,693 CitationsOPEN ACCESS

Deep learning for time series classification: a review

Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, Pierre-Alain Müller

S121920818. 20193,273 CitationsOPEN ACCESS

Recurrent Neural Networks for Multivariate Time Series with Missing Values

Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, Yan Liu

Scientific Reports. 20182,180 CitationsOPEN ACCESS

A global averaging method for dynamic time warping, with applications to clustering

François Petitjean, Alain Ketterlin, Pierre Gançarski

S414566. 20101,132 Citations

Data Mining for the Internet of Things: Literature Review and Challenges

Feng Chen, Pan Deng, Jiafu Wan, Daqiang Zhang, Athanasios V. Vasilakos, Xiaohui Rong