Research on Settlement Prediction of Building Foundation in Smart City Based on BP Network

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS
Luyao Wei
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引用次数: 0

Abstract

In the construction process of high-rise buildings, it is necessary to predict the settlement and deformation of the foundation, and the current prediction methods are mainly based on empirical theoretical calculations and methods and more accurate numerical analysis methods. In the face of the interference of complex and ever-changing terrain and parameter values on prediction methods, in order to accurately determine the settlement of building foundations, this study designed a smart city building foundation settlement prediction method based on BP neural network. Firstly, a real-time dynamic monitoring unit for building foundation settlement was constructed using Wireless Sensor Network (WSN) technology. Then, the monitoring data was used to calculate the relevant parameters of building foundation settlement through layer sum method. Finally, input the monitoring data into the BP network results, adjust the weights of the output layer and hidden layer using settlement related parameters, and output the settlement prediction results of the smart city building foundation through training. The study selected average error and prediction time as evaluation criteria to test the feasibility of the method proposed in this article. This method can effectively predict foundation settlement, with an average prediction error always less than 4% and a prediction process time always less than 49ms. Keyword—Smart city; intelligent architecture; foundation settlement; settlement prediction; BP neural network; parameter
基于BP网络的智慧城市建筑地基沉降预测研究
在高层建筑的施工过程中,需要对地基的沉降和变形进行预测,目前的预测方法主要是基于经验理论计算方法和较为精确的数值分析方法。面对复杂多变的地形和参数值对预测方法的干扰,为了准确判断建筑地基沉降,本研究设计了一种基于BP神经网络的智慧城市建筑地基沉降预测方法。首先,利用无线传感器网络(WSN)技术构建了建筑物地基沉降实时动态监测单元。然后,利用监测数据,通过分层求和法计算建筑地基沉降的相关参数。最后将监测数据输入到BP网络结果中,利用沉降相关参数调整输出层和隐含层的权重,通过训练输出智慧城市建设基础的沉降预测结果。选取平均误差和预测时间作为评价标准,检验本文方法的可行性。该方法能有效预测地基沉降,平均预测误差始终小于4%,预测过程时间始终小于49ms。Keyword-Smart城市;智能建筑;基础沉降;沉降预测;BP神经网络;参数
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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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