基于MF-DFA法和PSO-ELM模型的基坑变形规律研究

为准确掌握基坑变形的发展趋势,实现对基坑施工的准确指导,针对基坑变形序列的非线性和复杂性,提出利用MF-DFA法和PSO-ELM模型对基坑的变形规律进行研究。首先,利用MF-DFA法对基坑变形速率序列进行多重分形特征分析,以判断基坑的变形趋势;其次,利用PSO-ELM模型对基坑累计变形序列进行预测,得到基坑变形的预测值;最后,对比两变形序列的分析结果,综合判断基坑的变形趋势。同时,采用实例检验分析思路的准确性。结果表明:MF-DFA法能有效分析基坑变形速率序列的多重分形特征, PSO-ELM模型在基坑变形预测中也具有较高的预测精度,且两者对基坑变形规律的判断的一致性较好,相互佐证了两者分析结果的准确性,为基坑变形规律研究提供了一种新的思路。

Study on Deformation Law of Foundation Pit by Multifractal Detrended Fluctuation Analysis and Extreme Learning Machine Improved by Particle Swarm Optimization

In view of the nonlinearity and complexity of deformation series of foundation pit, we propose to research the deformation law of foundation pit by using multifractional detrended fluctuation analysis (MF-DFA) and extreme learning machine improved by particle swarm optimization (PSO-ELM). First of all, we adopt MF-DFA method to analyze the series of deformation rate of foundation pit; secondly, we employ PSO-ELM model to process the cumulative deformation series of foundation pit; finally, we can determine the comprehensive deformation trend of foundation pit by comparing the results of both deformation series. Conclusions imply that MF-DFA could effectively reflect the multifractional feature of deformation rate series, and meanwhile PSO-ELM model is of high accuracy in predicting deformation. The analysis results of the two methods are well consistent, which supports each other in accuracy.