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A platform for research: civil engineering, architecture and urbanism
Method for predicting lateral displacement of pile foundation of long-pile wharf
The invention discloses a long-piled wharf pile foundation lateral displacement prediction method. The method comprises the following steps that a long-piled wharf pile foundation lateral displacement deep learning sample set is obtained; establishing a deep learning prediction model for the lateral displacement of the pile foundation of the long-pile wharf; training the prediction model by adopting a deep learning sample set to obtain an optimized and trained deep learning prediction model for the lateral displacement of the pile foundation of the high-pile wharf; and inputting real-time acquired actual measurement data of the high-pile wharf pile into the optimized and trained high-pile wharf pile foundation lateral displacement deep learning prediction model to obtain a model output prediction result. Through mixing and correction of the measured data set and the finite element simulation data set of the lateral displacement of the pile foundation of the long-pile wharf, rich sample data is provided for establishing a deep learning prediction model for the lateral displacement of the pile foundation of the long-pile wharf, and the accuracy and reliability of lateral displacement prediction are guaranteed.
本发明公开了一种高桩码头桩基侧向位移预测方法，包括如下步骤：获取高桩码头桩基侧向位移深度学习样本集；建立高桩码头桩基侧向位移深度学习预测模型；采用深度学习样本集对预测模型进行训练得到优化训练后的高桩码头桩基侧向位移深度学习预测模型；将实时采集的高桩码头桩实测数据输入到优化训练后的高桩码头桩基侧向位移深度学习预测模型得到模型输出预测结果。本发明通过高桩码头桩基侧向位移实测数据集和有限元仿真数据集的混合和修正，为建立高桩码头桩基侧向位移深度学习预测模型提供的丰富的样本数据，保障了侧向位移预测的准确性和可靠性。
Method for predicting lateral displacement of pile foundation of long-pile wharf
The invention discloses a long-piled wharf pile foundation lateral displacement prediction method. The method comprises the following steps that a long-piled wharf pile foundation lateral displacement deep learning sample set is obtained; establishing a deep learning prediction model for the lateral displacement of the pile foundation of the long-pile wharf; training the prediction model by adopting a deep learning sample set to obtain an optimized and trained deep learning prediction model for the lateral displacement of the pile foundation of the high-pile wharf; and inputting real-time acquired actual measurement data of the high-pile wharf pile into the optimized and trained high-pile wharf pile foundation lateral displacement deep learning prediction model to obtain a model output prediction result. Through mixing and correction of the measured data set and the finite element simulation data set of the lateral displacement of the pile foundation of the long-pile wharf, rich sample data is provided for establishing a deep learning prediction model for the lateral displacement of the pile foundation of the long-pile wharf, and the accuracy and reliability of lateral displacement prediction are guaranteed.
本发明公开了一种高桩码头桩基侧向位移预测方法，包括如下步骤：获取高桩码头桩基侧向位移深度学习样本集；建立高桩码头桩基侧向位移深度学习预测模型；采用深度学习样本集对预测模型进行训练得到优化训练后的高桩码头桩基侧向位移深度学习预测模型；将实时采集的高桩码头桩实测数据输入到优化训练后的高桩码头桩基侧向位移深度学习预测模型得到模型输出预测结果。本发明通过高桩码头桩基侧向位移实测数据集和有限元仿真数据集的混合和修正，为建立高桩码头桩基侧向位移深度学习预测模型提供的丰富的样本数据，保障了侧向位移预测的准确性和可靠性。
Method for predicting lateral displacement of pile foundation of long-pile wharf
一种高桩码头桩基侧向位移预测方法
CHEN AIQING (author) / CHANG XUELING (author) / ZHU WEI (author) / WU WEILI (author) / XUAN MINGXUAN (author) / WANG SONGQI (author)
2023-03-14
Patent
Electronic Resource
Chinese
IPC:
G06F
ELECTRIC DIGITAL DATA PROCESSING
,
Elektrische digitale Datenverarbeitung
/
E02B
HYDRAULIC ENGINEERING
,
Wasserbau
/
E02D
FOUNDATIONS
,
Gründungen
/
G06N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
,
Rechnersysteme, basierend auf spezifischen Rechenmodellen
/
G06Q
Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke
,
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES
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