SOTAVerified

Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5201–5250 of 6748 papers

TitleStatusHype
A Novel Ensemble Deep Learning Model for Stock Prediction Based on Stock Prices and News—0
A Novel Framework for Handling Sparse Data in Traffic Forecast—0
A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series—0
A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes—0
A novel health risk model based on intraday physical activity time series collected by smartphones—0
A Novel Hybrid Framework for Hourly PM2.5 Concentration Forecasting Using CEEMDAN and Deep Temporal Convolutional Neural Network—0
A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting—0
A Novel Markov Model for Near-Term Railway Delay Prediction—0
A Novel Method Combines Moving Fronts, Data Decomposition and Deep Learning to Forecast Intricate Time Series—0
A Novel Method for Stock Forecasting based on Fuzzy Time Series Combined with the Longest Common/Repeated Sub-sequence—0
A novel method of fuzzy time series forecasting based on interval index number and membership value using support vector machine—0
A Novel Multi-Centroid Template Matching Algorithm and Its Application to Cough Detection—0
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network—0
Error Autocorrelation Objective Function for Improved System Modeling—0
A Novel Site-Agnostic Multimodal Deep Learning Model to Identify Pro-Eating Disorder Content on Social Media—0
A Novel Sparse Bayesian Learning and Its Application to Fault Diagnosis for Multistation Assembly Systems—0
A novel spectral method for inferring general diploid selection from time series genetic data—0
A novel stochastic model based on echo state networks for hydrological time series forecasting—0
A Novel Time-Varying Spectral Filtering Algorithm for Reconstruction of Motion Artifact Corrupted Heart Rate Signals During Intense Physical Activities Using a Wearable Photoplethysmogram Sensor—0
A Novel Trend Symbolic Aggregate Approximation for Time Series—0
Nonlinear Evolution via Spatially-Dependent Linear Dynamics for Electrophysiology and Calcium Data—0
A NOVEL VARIATIONAL FAMILY FOR HIDDEN NON-LINEAR MARKOV MODELS—0
An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting—0
Anticipating synchronization with machine learning—0
An Unsupervised Approach for Automatic Activity Recognition based on Hidden Markov Model Regression—0
An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending—0
An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples—0
A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection—0
Aortic Pressure Forecasting with Deep Sequence Learning—0
A Pattern Discovery Approach to Multivariate Time Series Forecasting—0
A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifiers—0
A Periodicity-based Parallel Time Series Prediction Algorithm in Cloud Computing Environments—0
Aphids, Ants and Ladybirds: a mathematical model predicting their population dynamics—0
A Pipeline for Graph-Based Monitoring of the Changes in the Information Space of Russian Social Media during the Lockdown—0
A platform for causal knowledge representation and inference in industrial fault diagnosis based on cubic DUCG—0
A plug-in graph neural network to boost temporal sensitivity in fMRI analysis—0
A point process approach for the classification of noisy calcium imaging data—0
A posteriori multi-stage optimal trading under transaction costs and a diversification constraint—0
A posteriori Trading-inspired Model-free Time Series Segmentation—0
Appformer: A Novel Framework for Mobile App Usage Prediction Leveraging Progressive Multi-Modal Data Fusion and Feature Extraction—0
Application of Common Spatial Patterns in Gravitational Waves Detection—0
Application of Deep Interpolation Network for Clustering of Physiologic Time Series—0
Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting—0
Application of Gaussian Process Regression to Koopman Mode Decomposition for Noisy Dynamic Data—0
Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series—0
Application of machine learning to gas flaring—0
Application of the Non-Hermitian Singular Spectrum Analysis to the exponential retrieval problem—0
Application of Time Series Analysis to Traffic Accidents in Los Angeles—0
Application Research On Real-Time Perception Of Device Performance Status—0
Applications of Machine Learning in Pharmacogenomics: Clustering Plasma Concentration-Time Curves—0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47—Unverified
2GRU-D - APC (n = 1)F127.3—Unverified
3GRU-APC (n = 1)F125.7—Unverified
4GRU-DF122.5—Unverified
5GRUF122.3—Unverified
6GRU-SimpleF122.2—Unverified
7GRU-MeanF122.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51—Unverified
2ViT% Test Accuracy98.11—Unverified
3FlexTCN-4% Test Accuracy97.73—Unverified
4MatchboxNet% Test Accuracy97.4—Unverified
5CKCNN (100k)% Test Accuracy95.27—Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13—Unverified