摘要
为提高沉降数据的准确预测并分析监测目标的变形趋势,避免重大工程事故的发生,建立了基于优化背景值的时变参数的灰色模型。首先,介绍了传统灰色GM(1,1)模型与新陈代谢灰色模型;其次,基于时变参数优化灰作用量的原理,建立了基于时变参数的灰色GM(1,1)模型和新陈代谢灰色模型,并采用黄金分割法优化灰色模型中权重参数,建立优化背景值的时变参数的灰色模型;最后,以某矿区地表沉降监测数据为例进行预测结果验证与精度评定。实验结果表明,基于优化背景值的时变参数的灰色模型预测精度最高,更加贴合地表监测数据变形趋势。
In order to improve the accuracy of settlement data,analyze the deformation trend of monitoring targets,and avoid the occurrence of major engineering accidents,we established a time-varying parameter grey model based on optimized background values.Firstly,we introduced the traditional grey GM(1,1)model and the metabolic grey model.Then,we established the grey GM(1,1)model and the metabolic grey model based on time-varying parameters based on the principle of optimizing the grey action quantity,used the golden section method to optimize the background value in the grey model,and established a grey model with time-varying parameters to optimize the background value.Finally,tak-ing the monitoring data of surface subsidence in a mining area for example,we verified the prediction results and evaluated the accuracy.The ex-perimental results show that this model has the highest prediction accuracy and is more suitable for the deformation trend of surface monitor-ing data.
作者
黄志强
李瑞红
HUANG Zhiqiang;LI Ruihong(Maoming Institute of Natural Resources Exploration and Mapping,Maoming 525000,China;Guangdong Surveying and Mapping Engineering Co.,Ltd.,Guangzhou 515700,China)
出处
《地理空间信息》
2024年第6期71-73,93,共4页
Geospatial Information
基金
广东省科技计划资助项目(2018B020207002)。
关键词
灰色模型
时变参数
背景值优化
精度检验
grey model
time-varying parameter
optimized background value
accuracy inspection
