现代隧道技术
現代隧道技術
현대수도기술
MODERN TUNNELLING TECHNOLOGY
2014年
6期
94-100
,共7页
地铁隧道%沉降预测%深基坑%支持向量机%蚁群优化算法%参数优化
地鐵隧道%沉降預測%深基坑%支持嚮量機%蟻群優化算法%參數優化
지철수도%침강예측%심기갱%지지향량궤%의군우화산법%삼수우화
Metro tunnel%Settlement prediction%Deep foundation pit%Support Vector Machine (SVM)%Ant Colony Optimization (ACO)%Parameter optimization
针对紧邻大型深基坑的地铁隧道因其变形影响因素复杂、变形控制严格而难以准确预测其沉降变形的问题，文章引入对小样本、复杂、非线性数据具有优越预测性能的支持向量机理论，并利用蚁群优化算法搜索支持向量机最优参数组合，建立了优化的支持向量机预测模型。应用该模型对南京市地铁1号线某段隧道的预测结果表明，该模型预测精度高，能够准确反映隧道变形趋势，可以满足紧邻大型深基坑地铁隧道沉降预测的要求。
針對緊鄰大型深基坑的地鐵隧道因其變形影響因素複雜、變形控製嚴格而難以準確預測其沉降變形的問題，文章引入對小樣本、複雜、非線性數據具有優越預測性能的支持嚮量機理論，併利用蟻群優化算法搜索支持嚮量機最優參數組閤，建立瞭優化的支持嚮量機預測模型。應用該模型對南京市地鐵1號線某段隧道的預測結果錶明，該模型預測精度高，能夠準確反映隧道變形趨勢，可以滿足緊鄰大型深基坑地鐵隧道沉降預測的要求。
침대긴린대형심기갱적지철수도인기변형영향인소복잡、변형공제엄격이난이준학예측기침강변형적문제，문장인입대소양본、복잡、비선성수거구유우월예측성능적지지향량궤이론，병이용의군우화산법수색지지향량궤최우삼수조합，건립료우화적지지향량궤예측모형。응용해모형대남경시지철1호선모단수도적예측결과표명，해모형예측정도고，능구준학반영수도변형추세，가이만족긴린대형심기갱지철수도침강예측적요구。
Due to the complex factors of and strict requirements for deformation control, it is difficult to accurate-ly predict the settlement of a metro tunnel adjacent to a deep large-scale foundation pit. In this paper, the Sup-port Vector Machine (SVM) theory is introduced for its excellent prediction capabilities regarding small sample, complex, and nonlinear data, and Ant Colony Optimization (ACO) was adopted to obtain an optimized SVM pre-diction model by selecting the most appropriate parameter combination. Based on the settlement prediction of a tunnel on Nanjing Metro Line 1, this model meets the requirements of settlement prediction for metro tunnels ad-jacent to deep large-scale foundation pits because of its sound prediction accuracy and accurate reflection of de-formation trends.
