| 基于粒子群优化的DGM（1,1）模型在基坑变形安全预测中的研究 |
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| 引用本文： | 陈家骐,华建兵,段园煜,司大雄,丁蕾,丁碧莹.基于粒子群优化的DGM（1,1）模型在基坑变形安全预测中的研究[J].中国安全生产科学技术,2019,15(3):161-166. |
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| 作者姓名： | 陈家骐 华建兵 段园煜 司大雄 丁蕾 丁碧莹 |
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| 作者单位： | （合肥学院 建筑工程系，安徽 合肥 230601） |
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| 基金项目： | 收稿日期: 2018-11-21 |
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| 摘 要： | 为确保基坑施工期间发生变形后能够正常使用，将变权缓冲算子结合DGM(1,1)模型构造出变权离散灰色模型，利用相对误差、后验差比，灰色绝对关联度3种精度检验法作为粒子群算法适应度建立模型，构造PSO-VWDGM(1,1)模型，并结合实际工程监测数据研究不同适应度对基坑变形预测精度的影响。研究结果表明:不同适应度函数对预测精度存在较大影响，以灰色绝对关联度作为适应度建立模型预测精度较高，可以更好应用在工程中。研究成果可为工程施工阶段的基坑变形预测、稳定性分析与灾害评估、预警提供参考。
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| 关 键 词： | 预测 粒子群 变权 DGM(1 1) 基坑变形 |
Study on DGM(1,1) model based on particle swarm optimization in predicting deformation safety of foundation pit |
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| CHEN Jiaqi,HUA Jianbing,DUAN Yuanyu,SI Daxiong,DING Lei,DING Bilei.Study on DGM(1,1) model based on particle swarm optimization in predicting deformation safety of foundation pit[J].Journal of Safety Science and Technology,2019,15(3):161-166. |
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| Authors: | CHEN Jiaqi HUA Jianbing DUAN Yuanyu SI Daxiong DING Lei DING Bilei |
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| Affiliation: | （Department of Civil Engineering，Hefei University，Hefei Anhui 230601，China） |
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| Abstract: | In order to ensure the deformation safety and normal operation of foundation pit during the construction process, the variable weight discrete grey model was constructed by using variable weight buffer operator combined with DGM (1, 1) model, then the model was established by taking three accuracy test methods including the relative error, posteriori error ratio and grey absolute correlation degree as the particle swarm algorithm fitness to construct the PSO-VWDGM(1,1) model, and the influence of different fitness on the prediction accuracy of foundation pit deformation was studied by combining with the practical engineering monitoring data. The results showed that different fitness functions had a great influence on the prediction accuracy, and the model established with the grey absolute correlation degree as the fitness had higher prediction accuracy, which can be better applied in the engineering. The results can provide reference for the safety, stability analysis, disaster assessment and early warning of foundation pit deformation in the construction stage of risk engineering. |
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| Keywords: | prediction particle swarm variable weight DGM(1 1) foundation pit |
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