# Time Series Analysis and Forecasting

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/time-series-analysis-and-forecasting/

## Facts

| Field | Value |
| --- | --- |
| Description | 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. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t12205 |
| Works | 62 |

## Topic papers all

Showing 15 of 62.

- [PhysioBank, PhysioToolkit, and PhysioNet](https://scholariq.org/papers/physiobank-physiotoolkit-and-physionet/)
- [Deep learning for time series classification: a review](https://scholariq.org/papers/deep-learning-for-time-series-classification-a-review/)
- [Fractal dynamics in physiology: Alterations with disease and aging](https://scholariq.org/papers/fractal-dynamics-in-physiology-alterations-with-disease-and-aging/)
- [Recurrent Neural Networks for Multivariate Time Series with Missing Values](https://scholariq.org/papers/recurrent-neural-networks-for-multivariate-time-series-with-missing-values-2/)
- [A global averaging method for dynamic time warping, with applications to clustering](https://scholariq.org/papers/a-global-averaging-method-for-dynamic-time-warping-with-applications-to/)
- [Applications of deep learning in stock market prediction: Recent progress](https://scholariq.org/papers/applications-of-deep-learning-in-stock-market-prediction-recent-progress/)
- [Predicting stock market index using fusion of machine learning techniques](https://scholariq.org/papers/predicting-stock-market-index-using-fusion-of-machine-learning-techniques/)
- [Data Mining for the Internet of Things: Literature Review and Challenges](https://scholariq.org/papers/data-mining-for-the-internet-of-things-literature-review-and-challenges/)
- [Weighted-permutation entropy: A complexity measure for time series incorporating amplitude information](https://scholariq.org/papers/weighted-permutation-entropy-a-complexity-measure-for-time-series-incorporating/)
- [Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion](https://scholariq.org/papers/hierarchical-aligned-cluster-analysis-for-temporal-clustering-of-human-motion/)
- [Incremental Linear Discriminant Analysis for Classification of Data Streams](https://scholariq.org/papers/incremental-linear-discriminant-analysis-for-classification-of-data-streams/)
- [Transfer learning for time series classification](https://scholariq.org/papers/transfer-learning-for-time-series-classification/)
- [Deep Computational Phenotyping](https://scholariq.org/papers/deep-computational-phenotyping/)
- [Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification](https://scholariq.org/papers/dynamic-time-warping-averaging-of-time-series-allows-faster-and-more-accurate/)
- [Recurrent Neural Networks for Multivariate Time Series with Missing Values](https://scholariq.org/papers/recurrent-neural-networks-for-multivariate-time-series-with-missing-values/)

## Topic primary papers

Showing 15 of 26.

- [PhysioBank, PhysioToolkit, and PhysioNet](https://scholariq.org/papers/physiobank-physiotoolkit-and-physionet/)
- [Deep learning for time series classification: a review](https://scholariq.org/papers/deep-learning-for-time-series-classification-a-review/)
- [Recurrent Neural Networks for Multivariate Time Series with Missing Values](https://scholariq.org/papers/recurrent-neural-networks-for-multivariate-time-series-with-missing-values-2/)
- [A global averaging method for dynamic time warping, with applications to clustering](https://scholariq.org/papers/a-global-averaging-method-for-dynamic-time-warping-with-applications-to/)
- [Data Mining for the Internet of Things: Literature Review and Challenges](https://scholariq.org/papers/data-mining-for-the-internet-of-things-literature-review-and-challenges/)
- [Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion](https://scholariq.org/papers/hierarchical-aligned-cluster-analysis-for-temporal-clustering-of-human-motion/)
- [Transfer learning for time series classification](https://scholariq.org/papers/transfer-learning-for-time-series-classification/)
- [Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification](https://scholariq.org/papers/dynamic-time-warping-averaging-of-time-series-allows-faster-and-more-accurate/)
- [Recurrent Neural Networks for Multivariate Time Series with Missing Values](https://scholariq.org/papers/recurrent-neural-networks-for-multivariate-time-series-with-missing-values/)
- [Forecast Methods for Time Series Data: A Survey](https://scholariq.org/papers/forecast-methods-for-time-series-data-a-survey/)
- [Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey](https://scholariq.org/papers/deep-learning-for-time-series-classification-and-extrinsic-regression-a-current/)
- [Generating Synthetic Time Series to Augment Sparse Datasets](https://scholariq.org/papers/generating-synthetic-time-series-to-augment-sparse-datasets/)
- [Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm](https://scholariq.org/papers/faster-and-more-accurate-classification-of-time-series-by-exploiting-a-novel/)
- [Time series extrinsic regression: Predicting numeric values from time series data.](https://scholariq.org/papers/time-series-extrinsic-regression-predicting-numeric-values-from-time-series-data/)
- [Optimizing dynamic time warping’s window width for time series data mining applications](https://scholariq.org/papers/optimizing-dynamic-time-warping-s-window-width-for-time-series-data-mining/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.