Abstract
In order to improve the prediction mode accuracy of wavelet neural network, a prediction model of optimized wavelet neural network based on mind evolutionary algorithm (MEA) is proposed. Firstly, using MEA with extremely strong global search ability to train and optimize the connection weight and the extension scale of the wavelet neural network. Secondly, establish the wavelet neural network using the optimized connection weight and the extension scale. After comparative study of the prediction mode of MEA optimized wavelet neural network, genetic algorithm (GA) optimized wavelet neural network (GAWNN) and not optimized wavelet neural network (WNN) on the prediction for short-term traffic flow, the results show that MEAWNN method has higher prediction accuracy than other two methods.
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Yu, Q., Wang, H. (2022). Application of MEA Optimized Wavelet Neural Network Model in Traffic Flow Prediction. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13338. Springer, Cham. https://doi.org/10.1007/978-3-031-06794-5_53
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DOI: https://doi.org/10.1007/978-3-031-06794-5_53
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