Verhulst反函数预测模型的改进及滑坡时间概率预测 Article Swipe
Mingxi Chen
,
Peijie Tao
,
Chuangbing Zhou
,
Qinghui Jiang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3799/dqkx.2023.003
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3799/dqkx.2023.003
摘要: 滑坡时间预测是滑坡灾害防治的重要组成部分,但由于滑坡演化存在不确定性,准确预测滑坡的发生极为困难.Verhulst反函数模型是一种常用的滑坡时间预测模型,但其存在计算起始时刻选择不当会造成监测数据拟合质量差和预测精度低的问题.针对这一不足,提出了一种改进的Verhulst反函数模型(MVIF模型),并进行近实时概率预测分析.结果表明:(1)MVIF模型改善了原模型对计算起始时刻选择苛刻的问题;(2)MVIF模型预测精度较高,在滑坡进入中等加速变形阶段之后可进行可靠的预测;(3)预测滑坡时间与破坏概率结合提供了一种新的滑坡预报准则.该研究可为蠕滑型滑坡的预警预报提供有价值的参考. 关键词: 滑坡 / 滑坡时间预测 / Verhulst反函数模型 / 模型改进 / 概率分析 / 预测决策 / 灾害
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https://openalex.org/W4400093661Canonical identifier for this work in OpenAlex
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Verhulst反函数预测模型的改进及滑坡时间概率预测Work title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-01-01Full publication date if available
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Mingxi Chen, Peijie Tao, Chuangbing Zhou, Qinghui JiangList of authors in order
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| abstract_inverted_index.滑坡时间预测 | 5 |
| abstract_inverted_index.Verhulst反函数模型 | 7 |
| abstract_inverted_index.滑坡时间预测是滑坡灾害防治的重要组成部分,但由于滑坡演化存在不确定性,准确预测滑坡的发生极为困难.Verhulst反函数模型是一种常用的滑坡时间预测模型,但其存在计算起始时刻选择不当会造成监测数据拟合质量差和预测精度低的问题.针对这一不足,提出了一种改进的Verhulst反函数模型(MVIF模型),并进行近实时概率预测分析.结果表明:(1)MVIF模型改善了原模型对计算起始时刻选择苛刻的问题;(2)MVIF模型预测精度较高,在滑坡进入中等加速变形阶段之后可进行可靠的预测;(3)预测滑坡时间与破坏概率结合提供了一种新的滑坡预报准则.该研究可为蠕滑型滑坡的预警预报提供有价值的参考. | 1 |
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