Multivariate time series forecasting

Neurocomputing, 2004
This paper proposes a temporal neuro-fuzzy system named ANFIS_unfolded_in_time which is designed to provide an environment that keeps temporal relationships between the variables and to forecast the future behavior of data by using fuzzy rules. It is a modification of ANFIS neuro-fuzzy model.
N. Arzu Sisman-Yilmaz, Ferda Nur Alpaslan, Lakhmi C. Jain +2 more
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A Robust Approach for Multivariate Time Series Forecasting

Proceedings of the Eighth International Symposium on Information and Communication Technology, 2017
Time series forecasting is often confronted with multivariate data, but few model is available in this situation. Besides, data distortion aggravates the difficulty to predict multivariate time series. To tackle such problems, we propose an approach based on convolutional neural network with a feature extraction layer added before convolution layer to ...
Ning Pang +3 more
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Deep Learning and Metaheuristic for Multivariate Time-Series Forecasting

2023
Time series forecasting is a widely used statistical technique that use past data to predict future values of variables. Its applications span across various fields, including finance, economics, and marketing. Multivariate time series forecasting, which involves two or more variables, is more complex than univariate time series forecasting and to ...
Zito F., Cutello V., Pavone M.
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machine learning cs.lg
fos: computer and information sciences
deep learning

multivariate time series
computer science - machine learning
forecasting

machine learning
medicine
artificial intelligence cs.ai