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Prediction of seawall foundation settlement based on the improved variable dimension fraction and artificial neural network model

机译:基于改进的变维分数和人工神经网络模型的海堤基础沉降预测

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Prediction of the seawall foundation settlement it important to the engineering maintenance and disaster prevention. A new method based on the improved variable dimension fraction (IVDF) and artificial neural network (ANN) was presented on the example of the seawall located in Zhejiang Province of China. The settlement displacement analysis for a single point located on the seawall was performed. The analysis consists of three stages: idea of IVDF — ANN model analysis, IVDF-ANN modeling, and deformation forecast. The resnlt proves that IVDF-ANN model makes good use of the self-similarity of fractal theory and the self-learning ability of artificial neural network, and the method has a degree of applicability.
机译:海堤基础沉降的预测对工程维护和防灾工作具有重要意义。以中国浙江省海堤为例,提出了一种基于改进的变维分数(IVDF)和人工神经网络(ANN)的新方法。对位于海堤上的单个点进行了沉降位移分析。分析包括三个阶段:IVDF的概念-ANN模型分析,IVDF-ANN建模和变形预测。结果表明,IVDF-ANN模型充分利用了分形理论的自相似性和人工神经网络的自学习能力,具有一定的适用性。

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