Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

Wind Speed Prediction Based on Time series Neural Network Algorithm

Authors
Zhaoyang Wang
Corresponding Author
Zhaoyang Wang
Available Online June 2016.
DOI
https://doi.org/10.2991/mecs-17.2017.101How to use a DOI?
Keywords
WindSPeed, TimeSeries, Neural Network, PredietionModels, BP, RBF
Abstract
This paper choose short-term prediction as the research content of the wind speed,the time series and neural network theory are uesd into to the wind speed prediction model.On the basis of BP model, ARMA-BP model is proposed.Then the ARMA-RBF model was established, makes the prediction error smaller.Simulation experimental results shows that using neural network to establish the sequence of the network, training time significantly shortened, network between predicted values and the real observation values of output doesn't appear too big deviation, the new training sample set fitting is good ,and prediction accuracy improved.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Zhaoyang Wang
PY  - 2016/06
DA  - 2016/06
TI  - Wind Speed Prediction Based on Time series Neural Network Algorithm
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SP  - 23
EP  - 26
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.101
DO  - https://doi.org/10.2991/mecs-17.2017.101
ID  - Wang2016/06
ER  -