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在降雨等外界诱发因素的综合作用下,滑坡位移预测是一个复杂的动力系统问题。利用三峡库区白家包滑坡综合监测数据,分析滑坡演化实时特征,提取影响滑坡变形的最相关因素,研究发现白家包滑坡为降雨主导型堆积层滑坡;采用自回归综合移动模型(ARIMA)模型进行拟合及预测,引入月累积降雨量对模型季节性趋势参数进行评估优化,对白家包滑坡72期月相对位移数据进行拟合及预测研究,最终模型结果和实测值的平均绝对误差和相关系数分别为2.873和0.983。研究结果表明,与传统经验法相比,优化参数模型更符合滑坡变形的一般规律。
Under the combined action of external factors such as rainfall, landslide displacement prediction is a complex dynamic system. Based on the integrated monitoring data of the Baijiaba landslide in the Three Gorges Reservoir area, the real-time characteristics of the landslide evolution were analyzed and the most relevant factors affecting the landslide deformation were extracted. The Baijiaba landslide was found to be a predominant rainfall-bearing landslide. The ARIMA The monthly cumulative rainfall is used to evaluate and optimize the model seasonal trend parameters. The monthly relative displacement data of the 72th Baijiaba landslide are fitted and predicted. The average absolute error between the final model and the measured value is The correlation coefficients were 2.873 and 0.983 respectively. The results show that compared with the traditional experience method, the optimization parameter model is more in line with the general law of landslide deformation.