基于BP神经网络的上市物流公司业绩预测模型

Prediction Model of Listed Logistics Company Based on BP Neural Network

为了科学预测上市物流公司的业绩,并利用BP神经网络的自我组织、自我学习和抗干扰等特性,建立了上市物流公司的业绩预测模型。首先以2010年的23家上市物流企业的数据为研究对象,然后采用BP算法建立预测模型对公司业绩进行预测,最后预测结果与它们的实际情况基本吻合,综合评估反映了上市物流公司的业绩。

In order to predict the performance of the listed logistics company, and using the BP neural network self or- ganize, self learning and anti interference characteristics, logistics listed company performance prediction model is set up. Regarding the data of first 23 listed logistics companies in 2010 as the research object, the BP algorithm is adopted to estab- lish prediction model to predict the performance of the company, finally forecast results are consistent with the actual situa- tion and their comprehensive evaluation, reflecting the performance of listed logistics companies.