山西科技
山西科技
산서과기
SHANXI KEJI
2014年
6期
85-86,89
,共3页
高速公路%路基沉降%神经网络模型%中误差
高速公路%路基沉降%神經網絡模型%中誤差
고속공로%로기침강%신경망락모형%중오차
expressway%roadbed settlement%neural network model%mean square error
高速公路施工中,路基沉降对工程质量有着重要的影响。但是影响路基沉降的因素很多,传统的线性预测模型很难将各种影响因素统一表达,BP神经网络模型可以将传统的函数关系式转化为高维的非线性映射,在路基沉降预测中得到广泛应用。以京津塘高速公路K131+610段工程为例,探讨了BP神经网络模型的最佳参数配合。
高速公路施工中,路基沉降對工程質量有著重要的影響。但是影響路基沉降的因素很多,傳統的線性預測模型很難將各種影響因素統一錶達,BP神經網絡模型可以將傳統的函數關繫式轉化為高維的非線性映射,在路基沉降預測中得到廣汎應用。以京津塘高速公路K131+610段工程為例,探討瞭BP神經網絡模型的最佳參數配閤。
고속공로시공중,로기침강대공정질량유착중요적영향。단시영향로기침강적인소흔다,전통적선성예측모형흔난장각충영향인소통일표체,BP신경망락모형가이장전통적함수관계식전화위고유적비선성영사,재로기침강예측중득도엄범응용。이경진당고속공로K131+610단공정위례,탐토료BP신경망락모형적최가삼수배합。
In the construction of expressway, the roadbed settlement has important influence on the construction quality. However, there are many factors influencing the roadbed settlement, it is very difficult for the traditional liner prediction model to make the unified expression of various influencing factors, and the BP neural?network model, which can transform the functional relation expression into the high-dimensional nonlinear mapping, is widely used in the prediction of roadbed settlement. Taking the project of K131+61 section of Beijing-Tianjin-Tanggu Expressway as an example, this paper probes into the optimum coordination of the parameters of BP neural network model.