The rapid development of edge computing drives the rapid development of stock market prediction service in terminal equipment. However, the traditional prediction service algorithm is not applicable in terms of stability and efficiency. In view of this challenge, an improved Elman neural network is proposed in this paper. Elman neural network is a typical dynamic recurrent neural network that can be used to provide the stock price prediction service. First, the prediction model parameters and build process are analysed in detail. Then, the historical data of the closing price of Shanghai composite index and the opening price of Shenzhen composite index are collected for training and testing, so as to predict the prices of the next trading day. Finally, the experiment results validate that it is effective to predict the short-term future stock price by using the improved Elman neural network model.

中文翻译：

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改进的Elman网络股票价格预测服务

边缘计算的快速发展推动了终端设备中股票市场预测服务的快速发展。然而，就稳定性和效率而言，传统的预测服务算法不适用。鉴于这一挑战，本文提出了一种改进的Elman神经网络。Elman神经网络是一种典型的动态递归神经网络，可用于提供股票价格预测服务。首先，详细分析了预测模型的参数和构建过程。然后，收集上海综合指数收盘价和深圳综合指数开盘价的历史数据进行训练和检验，以预测下一个交易日的价格。最后，