| 深基坑开挖位移多点监测模型及径向基函数神经网络计算中心的FCM确定 |
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| 引用本文： | 黄铭,刘俊.深基坑开挖位移多点监测模型及径向基函数神经网络计算中心的FCM确定[J].工业建筑,2012,42(3):80-83,158. |
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| 作者姓名： | 黄铭 刘俊 |
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| 作者单位： | 1. 合肥工业大学土木与水利工程学院,合肥,230009
2. 上海交通大学船舶海洋与建筑工程学院,上海,200240 |
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| 摘 要： | 为建立合理的基坑多测点位移监测模型,采用径向基函数神经网络(RBF)为基本框架,从位移力学机制选择网络输入层,以相关联的多个测点位移为输出层,发挥RBF网络非线性映射功能的同时,根据基坑的开挖进展和位移特征,采用有针对性的预选RBF计算中心与模糊C均值聚类(FCM)算法,共同确定计算中心。实例表明,该计算方法更具合理性,且能获得理想的训练和预测效果。
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| 关 键 词： | 多测点 基坑开挖 位移监测模型 预选RBF中心 FCM |
DEEP EXCAVATION MULTI-POINT DISPLACEMENT MONITORING MODEL AND DETERMINATION OF RBF CENTER BY FCM |
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| Huang Ming,Liu Jun.DEEP EXCAVATION MULTI-POINT DISPLACEMENT MONITORING MODEL AND DETERMINATION OF RBF CENTER BY FCM[J].Industrial Construction,2012,42(3):80-83,158. |
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| Authors: | Huang Ming Liu Jun |
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| Affiliation: | 1.School of Civil and Hydraulic Engineering,Hefei University of Technology,Hefei 230009,China; 2.School of Naval Architecture,Ocean and Civil Engineering,Shanghai Jiaotong University,Shanghai 200240,China) |
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| Abstract: | To establish reasonable deep excavation multi-point displacement monitoring model,radial basis function artificial neural network(RBF)was taken as frame.Its input layer came from displacement mechanical theory,and output layer was formed by interrelated multi-point displacement.Considering excavation and displacement characteristics,special preselecting RBF centers and Fuzzy C-means Algorithm(FCM)were used together to confirm RBF centers.Instances showed that these methods were more reasonable and possed good training and forecasting results. |
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| Keywords: | multi-point deep excavation displacement monitoring model preselecting RBF centers FCM |
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