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Time Series Prediction

9 papers with code ยท Time Series

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Cellular Traffic Prediction and Classification: a comparative evaluation of LSTM and ARIMA

3 Jun 2019

In this paper, we study the problem of network traffic traffic prediction and classification by employing standard machine learning and statistical learning time series prediction methods, including long short-term memory (LSTM) and autoregressive integrated moving average (ARIMA), respectively.

TIME SERIES TIME SERIES PREDICTION TRAFFIC PREDICTION

Patch Learning

1 Jun 2019

There have been different strategies to improve the performance of a machine learning model, e. g., increasing the depth, width, and/or nonlinearity of the model, and using ensemble learning to aggregate multiple base/weak learners in parallel or in series.

TIME SERIES TIME SERIES PREDICTION

A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting

30 May 2019

Next, a new multi-objective algorithm called MOHHO is first developed in this study, which are introduced to tune the parameters of ELM model with high forecasting accuracy and stability for air pollution series prediction, simultaneously.

AIR POLLUTION PREDICTION TIME SERIES TIME SERIES PREDICTION

Robust guarantees for learning an autoregressive filter

23 May 2019

The optimal predictor for a linear dynamical system (with hidden state and Gaussian noise) takes the form of an autoregressive linear filter, namely the Kalman filter.

TIME SERIES TIME SERIES PREDICTION

Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning

17 May 2019

We present a collection of results on how to enforce constraints coming from the dynamical system in order to accelerate the training of deep neural networks to represent the flow map of the system as well as increase their predictive ability.

TIME SERIES TIME SERIES PREDICTION

Similarity Grouping-Guided Neural Network Modeling for Maritime Time Series Prediction

13 May 2019

Reliable and accurate prediction of time series plays a crucial role in maritime industry, such as economic investment, transportation planning, port planning and design, etc.

TIME SERIES TIME SERIES PREDICTION

Large-Scale Spectrum Occupancy Learning via Tensor Decomposition and LSTM Networks

10 May 2019

A new paradigm for large-scale spectrum occupancy learning based on long short-term memory (LSTM) recurrent neural networks is proposed.

TIME SERIES TIME SERIES PREDICTION

The Expressive Power of Gated Recurrent Units as a Continuous Dynamical System

ICLR 2019

Gated recurrent units (GRUs) were inspired by the common gated recurrent unit, long short-term memory (LSTM), as a means of capturing temporal structure with less complex memory unit architecture.

TIME SERIES TIME SERIES PREDICTION

DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction

16 Apr 2019

The key to solve this problem is to capture the spatial correlations at the same time, the spatio-temporal relationships at different times and the long-term dependence of the temporal relationships between different series.

TIME SERIES TIME SERIES PREDICTION

Two-phase flow regime prediction using LSTM based deep recurrent neural network

30 Mar 2019

Long short-term memory (LSTM) and recurrent neural network (RNN) has achieved great successes on time-series prediction.

TIME SERIES TIME SERIES PREDICTION