基于改进的变权缓冲灰色模型在沉降预测中的应用  

Application of Improved Variable Weight Buffer Grey Model in Settlement Prediction

作　　者：王德法[1] 刘镇瑜 雒亿平 朱梦雲 WANG De-fa;LIU Zhen-yu;LUO Yi-ping;ZHU Meng-yun(School of Civil and Architectural Engineering,Xi'an University of Technology,Xi'an 710048,China;College of Water Resources and Hydropower,Xi'an University of Technology,Xi'an 710048,China)

机构地区：[1]西安理工大学土木建筑工程学院,西安710048 [2]西安理工大学水利水电学院,西安710048

出　　处：《科学技术与工程》2023年第13期5677-5684,共8页Science Technology and Engineering

摘　　要：针对灰色模型在中后期沉降预测中的精度问题,提出了单、双权幂函数弱化缓冲算子,并结合变权背景值建立改进的变权缓冲GM(1,1)模型。证明了新算子能提高光滑性、缩小级比偏差,实现对原始沉降数据的预处理。对于模型中的权值采用以还原值与原始值平均相对误差最小为目标的粒子群优化算法确定。最后,以高填方机场地表沉降数据预测为例,验证所提改进模型的有效性。结果表明:新算子能够有效弱化沉降序列受到的冲击扰动影响,结合变权背景值能显著提高灰色模型在中后期沉降预测中的精度。此外,对新算子的权值进行限定后,可得到两种不同的变权弱化缓冲算子。Aiming at the accuracy problem of grey model in the settlement prediction in the middle and later period,a double weight power function weakening buffer operator was proposed,and an improved variable weight buffer GM(1,1)model was established by combining the variable weight background value.It is proved that the new operator can improve the smoothness,reduce the stage ratio deviation,and achieve the preprocessing of the original settlement data.The weights in the model were determined by the particle swarm optimization algorithm with the objective of minimizing the average relative error between the restored value and the original value.Finally,the effectiveness of the improved model was verified by using a high fill airport surface settlement data prediction as an example.The results show that the new operator can effectively weaken the impact disturbance on the settlement sequence,and the combination of variable weight background value can significantly improve the accuracy of the gray model in the settlement prediction in the middle and later stages.In addition,after the weight value of the new operator is limited,two different variable weight weakening buffer operators can be obtained.

关 键 词：变权缓冲GM(1 1)模型 变权弱化缓冲算子 变权背景值 粒子群算法 沉降预测 

分 类 号：TU470[建筑科学—结构工程]