基于PCA-BP神经网络算法的企业资产预测与分析

Prediction and analysis of enterprise assets based on PCA-BP neural network algorithm

采用主成分分析法,对2010—2019年我国规模以上工业企业资产总额以及相关数据进行分析,得出我国规模以上工业企业自2010年以后总资产及其他指标发展状况.将2010—2018年资产总额的时间序列数据作为训练数据,建立神经网络预测模型,利用BP神经网络分析方法对2019年资产总额进行预测,最终得到较为准确的估计结果,为我国规模以上工业企业资产总额预测提供了合理化、科学化理论支持.

Using the principal component analysis method,the total assets and relevant data of Chinese industrial enterprises above designated size from 2010 to 2019 were analyzed,and the development status of total assets and other indicators of Chinese industrial enterprises above designated size since 2010 was obtained.Taking the time series data of total assets from 2010 to 2018 as the training data,the neural network prediction model is established,and the BP neural network analysis method is used to predict the total assets in 2019,a more accurate estimation result was obtained,which provides a reasonable and scientific theoretical support for the prediction of total assets of industrial enterprises above designated size in China.