基于改进的GWO和LSTM的加密货币预测模型OA

Cryptocurrency is a digital exchange medium using blockchain technology,which has the advantages of safe and transparent transaction process and immutable transaction records.Although cryptocurrency is recognized by many financial institu-tions,the uncertainty of its price poses a major risk to investment,so the price prediction of cryptocurrency has become a research hotspot.This paper proposes a cryptocurrency prediction model based on GWO,LSTM,and Attention mechanism.This paper uses the Attention mechanism to improve the LSTM model,which improves the mining performance of the long-term dependence of the LSTM model on time series data,thereby improving the prediction accuracy of the model.This paper designs an improved algorithm of GWO,IGWO,to improve the optimization performance of the GWO algorithm for hyperparameters of the network model.Finally,the IGWO algorithm is used to optimize the hyperparameters of LSTM-Attention to further improve the prediction accuracy of the model.Compared with CNN,RNN,LSTM single model,the prediction accuracy of the model proposed in this paper is significantly improved.