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Research on the Pit Overall Stability Intelligent Forecasting and Early Warning Method Based on GRNN

机译:基于GRNN的基坑整体稳定性智能预测预警方法研究。

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摘要

To ensure the safety of pit, proposed the intelligent forecasting and early warning method. Patent on one such early warning method, GRNN, is discussed. A brief review of the status about models of soil and excavation stability studies, pointed out that it is necessary that pit slope stability is conducted by the intelligent algorithm. With specific examples of projects, used HS model of PLAXIS geotechnical engineering software to analyze finite element including seepage calculation and get the training data and test data required by generalized regression neural network. With the date made inversion calculation of the soil parameters. Then the strength reduction was combined with the warning grading thought to build intelligent early warning system to predict excavation stability. The study pointed out that the pit overall stability intelligent forecasting and early warning method can effectively control error and avoid ambiguity forecast.
机译:为保证矿井安全,提出了智能化的预警预警方法。讨论了一种这样的预警方法GRNN的专利。简要回顾了土体模型和基坑开挖稳定性研究的现状,指出有必要利用智能算法进行基坑边坡稳定。通过具体的项目实例,使用PLAXIS岩土工程软件的HS模型对包括渗流计算在内的有限元进行分析,并获得广义回归神经网络所需的训练数据和测试数据。用日期作反演计算土壤参数。然后将强度折减与预警等级思想相结合,构建智能的预警系统,以预测开挖稳定性。研究指出,矿井整体稳定性智能预测预警方法可以有效控制误差,避免模棱两可的预测。

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