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Subway station foundation pit wall lateral displacement prediction method considering multiple factors
The invention discloses a subway station foundation pit wall lateral deformation prediction system considering multiple factors. The system comprises the steps that S1, foundation pit deformation influence factors are identified; s2, performing standardization processing on the deformation influence factor data; s3, carrying out weight calculation and empowerment on a model primary function; s4, establishing a foundation pit deformation prediction model and evaluating a prediction result; and S5, analyzing and quantifying the sensitivity to the deformation influence factors based on the prediction evaluation model. The method has the advantages that various deformation influence factors can be comprehensively considered based on actual monitoring data of the foundation pit through data learning, and the deformation behavior of the foundation pit is reasonably predicted; the deformation prediction accuracy and applicability of the long-strip-shaped subway station deep foundation pit are higher; a large amount of monitoring data is automatically processed, high efficiency and automation are achieved, the lateral deformation behavior of the foundation pit can be fed back and predicted in time, and the method has important significance on the construction quality and safety of the foundation pit.
本发明公开了一种考虑多元因素的地铁车站基坑墙体侧向变形预测系统,系统包括:S1、基坑变形影响因素识别;S2、变形影响因素数据标准化处理;S3、模型基函数权重计算及赋权;S4、建立基坑变形预测模型并评价预测结果;S5、基于预测评价模型分析量化对变形影响因子的敏感性。本发明的优点是:通过数据学习,基于基坑实际监测数据,能够全面考虑各种变形影响因子,合理预测基坑变形行为;对长条形地铁车站深基坑的变形预测准确性和适用性更强;自动处理大量监测数据,实现高效、自动化,能够及时反馈预测基坑的侧向变形行为,对基坑施工质量和安全具有重要意义。
Subway station foundation pit wall lateral displacement prediction method considering multiple factors
The invention discloses a subway station foundation pit wall lateral deformation prediction system considering multiple factors. The system comprises the steps that S1, foundation pit deformation influence factors are identified; s2, performing standardization processing on the deformation influence factor data; s3, carrying out weight calculation and empowerment on a model primary function; s4, establishing a foundation pit deformation prediction model and evaluating a prediction result; and S5, analyzing and quantifying the sensitivity to the deformation influence factors based on the prediction evaluation model. The method has the advantages that various deformation influence factors can be comprehensively considered based on actual monitoring data of the foundation pit through data learning, and the deformation behavior of the foundation pit is reasonably predicted; the deformation prediction accuracy and applicability of the long-strip-shaped subway station deep foundation pit are higher; a large amount of monitoring data is automatically processed, high efficiency and automation are achieved, the lateral deformation behavior of the foundation pit can be fed back and predicted in time, and the method has important significance on the construction quality and safety of the foundation pit.
本发明公开了一种考虑多元因素的地铁车站基坑墙体侧向变形预测系统,系统包括:S1、基坑变形影响因素识别;S2、变形影响因素数据标准化处理;S3、模型基函数权重计算及赋权;S4、建立基坑变形预测模型并评价预测结果;S5、基于预测评价模型分析量化对变形影响因子的敏感性。本发明的优点是:通过数据学习,基于基坑实际监测数据,能够全面考虑各种变形影响因子,合理预测基坑变形行为;对长条形地铁车站深基坑的变形预测准确性和适用性更强;自动处理大量监测数据,实现高效、自动化,能够及时反馈预测基坑的侧向变形行为,对基坑施工质量和安全具有重要意义。
Subway station foundation pit wall lateral displacement prediction method considering multiple factors
一种考虑多元因素的地铁车站基坑墙体侧移预测方法
JIANG XIAOTIAN (author) / FU WEI (author) / HU SHILIANG (author) / TIAN JING (author) / ZHANG XIAO (author)
2024-09-17
Patent
Electronic Resource
Chinese
IPC:
G06Q
Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke
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DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES
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E02D
FOUNDATIONS
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Gründungen
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G06F
ELECTRIC DIGITAL DATA PROCESSING
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Elektrische digitale Datenverarbeitung
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