安全与环境工程2024，Vol.31Issue(6)：169-178,10.DOI:10.13578/j.cnki.issn.1671-1556.20231102
基于BP神经网络的周口店遗址裂缝变形监测数据分析与预测
Analysis and prediction of crack deformation monitoring data of Zhoukoudian site based on back propagation neural network
摘要
Abstract
Zhoukoudian site is one of the sites with rich connotation,complete materials and scientific research value in the Pleistocene ancient human sites around the world.It is the scientific research base of paleoanthropology,Paleolithic archaeology and Quaternary geology in China.Under the long-term protection and monitoring of Zhoukoudian site by the state,a large number of different types of monitoring data have been retained,but there has been a lack of deep data mining and efficient utilization of these monitoring data for a long time.Based on the geological data and field investigation of Zhoukoudian site,this paper uses the back propagation neural network method and the time series prediction principle,and combines the original monitoring data of Zhoukoudian site to predict the fracture deformation of the third site of Zhoukoudian site.The prediction research is divided into two aspects:completing missing data and predicting future data.The results show that the prediction model based on BP neural network and the monitoring data of Zhoukoudian site has high prediction accuracy after a lot of data training,and can realize the completion of the missing part of the monitoring data and the prediction of the future development of the monitoring data through prediction.The research results provide a new processing method for the monitoring data of Zhoukoudian site,and enrich the processing means of a large number of monitoring data by Zhoukoudian site monitoring center.The early warning system of crack deformation in the third site of Zhoukoudian site is of great significance to the follow-up preventive protection work of Zhoukoudian site.关键词
裂缝变形/BP神经网络/时间序列预测/周口店遗址Key words
crack deformation/back propagation neural network/time series prediction/Zhoukoudian site分类
资源环境引用本文复制引用
康凯,孟雨萱,郑健,付前方,许国平,崔德山..基于BP神经网络的周口店遗址裂缝变形监测数据分析与预测[J].安全与环境工程,2024,31(6):169-178,10.基金项目
国家自然科学基金项目(42277171) （42277171）
