基于组合预测模型的滑坡变形趋势研究OACSTPCD
Research on Landslide Deformation Trends Based on Combination Prediction
为实现滑坡变形的高精度预测,基于滑坡变形监测成果,先以支持向量回归、RReliefF 算法、鲸鱼优化算法及 Arima模型为基础,构建滑坡变形组合预测模型;再利用多重分形消除趋势波动分析和 Spearman秩次检验,研究滑坡变形的多标度特征.结果表明,通过不断组合优化处理,能显著提高滑坡变形预测精度,且经外推预测,D1～D3 监测点的现有速率相对更大,且预测速率较现有速率的减小幅度依次为 21.61%、12.95%和 6.54%,D4 监测点的预…查看全部>>
To achieve high-precision prediction of landslide deformation,based on the monitoring results of landslide deformation,a combined prediction model for landslide deformation is constructed using support vector regression,RReliefF algorithm,whale optimization algorithm,and Arima model.Then,the multi-scale characteristics of landslide deformation are studied using multifractal elimination trend fluctuation analysis and Spearman rank test.The results show that,t…查看全部>>
王旭阳;张莹
河南省第四地质勘查院有限公司,河南 郑州 450001河南省第四地质勘查院有限公司,河南 郑州 450001
地质学
滑坡变形监测组合预测模型支持向量回归鲸鱼优化算法多重分形消除趋势波动分析Spearman秩次检验
landslidedeformation monitoringcombination prediction modelsupport vector regressionwhale optimization algorithmmultifractal elimination trend fluctuation analysisSpearman rank test
《水力发电》 2024 (10)
42-46,94,6
河南省财政厅2022年重点生态保护修复治理项目(豫财环资[2022]67号)
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