DYNAMIC INTERACTION NETWORKS VERSUS LOCAL TREND MODELS FOR MULTIPLE TIME-SERIES PREDICTION

Cybernetics & Systems ◽

10.1080/01969722.2011.541210 ◽

2011 ◽

Vol 42 (2) ◽

pp. 100-123 ◽

Author(s):

Harya Widiputra ◽

Russel Pears ◽

Nikola Kasabov

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Dynamic Interaction ◽

Interaction Networks ◽

Multiple Time ◽

Multiple Time Series ◽

Download Full-text

A New Approach to Multiple Time Series Prediction Using MIMO Fuzzy Aggregation Models with Modular Neural Networks

International Journal of Fuzzy Systems ◽

10.1007/s40815-019-00642-w ◽

2019 ◽

Vol 21 (5) ◽

pp. 1629-1648 ◽

Author(s):

Jesus Soto ◽

Oscar Castillo ◽

Patricia Melin ◽

Witold Pedrycz

Keyword(s):

Neural Networks ◽

Time Series ◽

Time Series Prediction ◽

Multiple Time ◽

Multiple Time Series ◽

New Approach ◽

Modular Neural Networks ◽

Fuzzy Aggregation

Download Full-text

Selection of Distributed Sensors for Multiple Time Series Prediction

The 2006 IEEE International Joint Conference on Neural Network Proceedings ◽

10.1109/ijcnn.2006.1716527 ◽

2006 ◽

Author(s):

C. Walgampaya ◽

M. Kantardzic

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Multiple Time ◽

Multiple Time Series ◽

Distributed Sensors ◽

Download Full-text

Evolving integrated multi-model framework for on line multiple time series prediction

Evolving Systems ◽

10.1007/s12530-012-9069-y ◽

2012 ◽

Vol 4 (2) ◽

pp. 99-117 ◽

Author(s):

Russel Pears ◽

Harya Widiputra ◽

Nikola Kasabov

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Multiple Time ◽

Multiple Time Series ◽

Model Framework ◽

Download Full-text

Multiple Time-Series Prediction through Multiple Time-Series Relationships Profiling and Clustered Recurring Trends

Advances in Knowledge Discovery and Data Mining - Lecture Notes in Computer Science ◽

10.1007/978-3-642-20847-8_14 ◽

2011 ◽

pp. 161-172 ◽

Author(s):

Harya Widiputra ◽

Russel Pears ◽

Nikola Kasabov

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Multiple Time ◽

Multiple Time Series

Download Full-text

Selection of Distributed Sensors for Multiple Time Series Prediction

The 2006 IEEE International Joint Conference on Neural Network Proceedings ◽

10.1109/ijcnn.2006.247298 ◽

2006 ◽

Author(s):

C. Walgampaya ◽

M. Kantardzic

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Multiple Time ◽

Multiple Time Series ◽

Distributed Sensors ◽

Download Full-text

Genetic algorithms on multiple time series prediction

10.14711/thesis-b571485 ◽

1997 ◽

Author(s):

Kin Hong Cheung

Keyword(s):

Time Series ◽

Genetic Algorithms ◽

Time Series Prediction ◽

Multiple Time ◽

Multiple Time Series

Download Full-text

Non-linear modeling of variables relationship in multiple time-series data with extended dynamic interaction network

2017 International Conference on Sustainable Information Engineering and Technology (SIET) ◽

10.1109/siet.2017.8304147 ◽

2017 ◽

Author(s):

Harya Widiputra ◽

Elliana Gautama ◽

Marsudi Kisworo

Keyword(s):

Time Series ◽

Time Series Data ◽

Interaction Network ◽

Dynamic Interaction ◽

Series Data ◽

Multiple Time ◽

Multiple Time Series ◽

Linear Modeling ◽

Extended Dynamic

Download Full-text

BRIEF: Bayesian Regression of Infinite Expert Forecasters for single and multiple time series prediction

2015 54th IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc.2015.7402089 ◽

2015 ◽

Author(s):

Ming Jin ◽

Costas J. Spanos

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Bayesian Regression ◽

Multiple Time ◽

Multiple Time Series

Download Full-text

A granular recurrent neural network for multiple time series prediction

Neural Computing and Applications ◽

10.1007/s00521-021-05791-4 ◽

2021 ◽

Author(s):

Stefania Tomasiello ◽

Vincenzo Loia ◽

Abdul Khaliq

Keyword(s):

Neural Network ◽

Time Series ◽

Recurrent Neural Network ◽

Time Series Prediction ◽

Multiple Time ◽

Multiple Time Series

Download Full-text

Improving Multiple Time Series Forecasting with Data Stream Mining Algorithms

2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ◽

10.1109/smc42975.2020.9283059 ◽

2020 ◽

Author(s):

Marcos Alberto Mochinski ◽

Jean Paul Barddal ◽

Fabricio Enembreck

Keyword(s):

Time Series ◽

Data Stream ◽

Time Series Forecasting ◽

Data Stream Mining ◽

Multiple Time ◽

Multiple Time Series ◽

Stream Mining ◽

Mining Algorithms

Download Full-text