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基于t分布和线性编程优化算法的碎片流风险评估的组合权重方法
Li Li1, Hanjie Lin1, Yue Qiang1
1Civil Engineering College, Chongqing Three Gorges University, Wanzhou, Chongqing, China.
PloS one
|June 14, 2024
概括
本研究引入了一种使用t分布和线性编程优化算法 (LPOA) 的新型废料流风险评估方法,通过考虑指标重要性和废料流频率来更准确地评估风险,改进了传统技术.
科学领域:
- 地质科学 地质科学
- 自然危害评估自然危害评估
- 风险管理 风险管理
背景情况:
- 碎片流风险评估对于预防和控制项目至关重要.
- 现有的方法往往过度强调客观或主观指标,忽视指标相互作用.
- 像EWM和VCM这样的传统方法忽视了碎片流动频率对风险的影响.
研究的目的:
- 为碎片流风险评估提出一种新的重量计算方法.
- 整合t分布和线性编程优化算法 (LPOA) 进行可靠的权重.
- 通过避免过度强调单一指标并纳入频率效应来提高风险评估的准确性.
主要方法:
- 使用分析层次过程 (AHP),重法 (EWM) 和变化系数法 (VCM) 获得的初始权重.
- 在各种置信级别使用t分布确定权重区间.
- 用LPOA计算的最终重量,在90%的置信区间内,用于碎片流风险评分.
主要成果:
- 拟议的方法避免了与EWM和VCM相比过度强调个别指标.
- 聚变权衡方法有效地纳入了碎片流动频率,这是EWM和VCM错过的一个因素.
- 在北川县,评估了72个碎片流,其中大多数被归类为中度和轻度风险 (8高,24中度,40轻度).
结论:
- 开发的聚变权重方法为碎片流风险评估提供了更合理,更全面的方法.
- 该方法能够避免单一指标偏差并包括频率效应的能力提高了其适用性.
- 结果为组合权重方法和碎片流风险管理策略提供了宝贵的见解.
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