Echo state network based prediction method and prediction device

Abstract

The embodiment of the invention provides an echo state network based prediction method and a prediction device, and relates to the field of computers. The prediction method and prediction device can effectively improve the prediction performance of the ESN (Echo State Network), and increase the speed and the accuracy of prediction. The prediction method comprises the following steps: firstly, establishing an echo state network prediction model, wherein nerve cells in a dynamic pool of the echo state network prediction model serves as wavelet nerve cells; acquiring a training set according to the input data, utilizing the training set to carry out prediction training on the echo state network prediction model, and obtaining the trained prediction model; predicting according to the trained prediction model, so as to obtain output data. The echo state network based prediction method and the prediction device disclosed by the embodiment of the invention can be applied to prediction of nonlinear chaotic time series data.

Description

technical field [0001] The invention relates to the field of computers, in particular to a prediction method and a prediction device based on an echo state network. Background technique [0002] The use of neural networks to predict nonlinear systems has achieved good results and has been widely used. Echo State Network (ESN) is a new type of recurrent network structure and recurrent network learning method. ESN has a large-scale internal neuron, which makes it have good short-term memory ability. In the chaotic time series prediction task Much better than traditional neural networks. [0003] In the process of realizing the prediction of the above-mentioned nonlinear system, the inventors found that there are at least the following problems in the prior art: [0004] In the prediction of nonlinear system using ESN echo state network, the prediction speed in classical ESN echo state network is relatively slow, and the prediction accuracy cannot meet the requirements. Con...

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Problems solved by technology

[0004] In the prediction of nonlinear systems using the ESN echo state network, the prediction speed in the classic ESN echo state network is relatively slow, and the prediction accuracy cannot meet the requirements

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