摘要
工程产品价格的波动是很多从业人员所关注的重点领域,如何准确地预测价格走势带来收益对企业和个人都具有十分重要的意义。围绕该问题,本文以某工程产品的价格为研究对象,采用基于TensorFlow框架的递归神经网络算法对价格未来指数进行评价,根据产品的初始价格建立工程产品价格预测模型,以此对工程产品价格发展趋势进行预测模拟。实验结果表明,采用RNN产品价格预测模型得到的预测结果的准确率可达84%,为提高工程产品价格预测精度提供了建设性依据。
The price fluctuation of engineering products is the key field that many practitioners pay attention to.How to accurately predict the price trend to bring benefits is of great significance to enterprises and individuals.To solve this problem,this paper takes the price of an engineering product as the research object,adopts the recursive neural network algorithm based on TensorFlow framework to evaluate the price future index,and establishes the price prediction model of engineering product according to the initial price of the product,so as to predict and simulate the price development trend of engineering product.Experimental results show that the accuracy of prediction results obtained by using RNN stock prediction model can reach 84%,which provides a constructive basis for improving the prediction accuracy of engineering product price.
作者
丁方一
Ding Fangyi(Jilin University of Finance and Economics,School of Management Science and Information Engineering,Changchun 130117,China)
出处
《科学技术创新》
2022年第7期77-80,共4页
Scientific and Technological Innovation
关键词
工程产品
RNN
预测
Engineering products
RNN
Prediction
