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基于线性编程可变重量云模型的崩风险评估
Xiaoyi Zhou1, Ke Hu1, Tingqiang Zhou1
1Department of Civil Engineering, Chongqing Three Gorges University, Wanzhou, Chongqing, China.
PloS one
|December 16, 2024
概括
这项研究引入了一种用于评估山区地质崩塌风险的新方法. 新方法通过整合线性编程和云模型来提高准确性,识别了65%的分析崩是非常危险的.
科学领域:
- 地质工程是地质工程.
- 灾害风险评估 灾害风险评估
- 地质技术工程 地质技术工程
背景情况:
- 崩塌风险评估对于管理山区地质灾害至关重要.
- 传统的崩危险评估方法面临的局限性是由于指标分配的可变性和无法同时处理数据模两可和随机性.
- 现有的关于崩危险评估的研究是有限的,阻碍了风险管理的进步.
研究的目的:
- 通过结合线性编程理论和云模型,开发一个先进的崩风险评估模型.
- 提高崩风险评估的准确性和可靠性,以预防和控制地质灾害.
- 解决传统指标分配和综合评估方法的局限性.
主要方法:
- 使用改进的分析层次过程,权方法和变化系数方法确定评估指数的权重区间.
- 采用线性编程算法,为每个崩样本选择特定的重量,以最大限度地提高间隔内的风险.
- 建立基于云模型的全面评估模型,以确定崩的风险水平.
主要成果:
- 开发的方法应用于G4217温chuan-lixian部分的20个崩样本.
- 评估结果显示,13个样本 (65%) 是极度危险的,2个 (10%) 是高度危险的,4个 (20%) 是中度危险的,1个 (5%) 是低危险的.
- 该方法的可靠性和合理性通过与其他评估技术和现场调查数据进行比较来验证,显示了与实际条件更好的协调.
结论:
- 综合线性编程和云模型方法为崩风险评估提供了更可靠和更合理的方法.
- 这种先进的模型有效地处理与指标数据固有的模糊性和随机性,优于传统方法.
- 这些发现为加强山区地质灾害预防和控制战略提供了宝贵的工具.
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