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Comparison Of Feedforward And Feedback Neural Network Architectures For Short Term Wind Speed Prediction, Ganesh K. Venayagamoorthy, Richard L. Welch, Stephen M. Ruffing

Electrical and Computer Engineering Faculty Research & Creative Works

This paper compares three types of neural networks trained using particle swarm optimization (PSO) for use in the short term prediction of wind speed. The three types of neural networks compared are the multi-layer perceptron (MLP) neural network, Elman recurrent neural network, and simultaneous recurrent neural network (SRN). Each network is trained and tested using meteorological data of one week measured at the National Renewable Energy Laboratory National Wind Technology Center near Boulder, CO. Results show that while the recurrent neural networks outperform the MLP in the best and average case with a lower overall mean squared error, the MLP …