Short-term wind speed prediction based on MLP and NARX network models
| Main Authors: | Yousra Amellas, Outman El Bakkali, Abdelouahed Djebil, Adil Echchelh |
|---|---|
| Format: | Article |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/5524157 |
Daftar Isi:
- The article aims to predict the wind speed by two artificial neural network’s models. The first model is a multilayer perceptron (MLP) treated by backpropagation algorithm and the second one is a recurrent neuron network type, processed by the NARX model. The two models having the same Network’s structure, which they are composed by 4 Inputs layers (Wind Speed, Pressure Temperature and Humidity), an intermediate layer defined by 20 neurons and an activation function, as well as a single output layer characterized by wind speed and a linear function. NARX shows the best results with a regression coefficient R = 0.984 et RMSE = 0.314.