使用信息敏感度方法和可变模糊模型优化水质评价指数,用于中国的郭河
Shuoya Cheng1, Peigui Liu2, Mei Yao3
1School of Civil Engineering, Hefei University of Technology, Hefei, 230009, China.
Environmental science and pollution research international
|February 8, 2024
概括
优化水质评估包括减少指标. 信息敏感度方法有效地简化了系统,保持了河水质量评估的准确性和提高了效率.
科学领域:
- 环境科学 环境科学
- 水资源管理 水资源管理
- 数据分析 数据分析
背景情况:
- 越来越多的水质指标提高了计算需求.
- 指数选方法对于优化水质评估准确性和效率至关重要.
- 简化复杂的数据集对于实际的水质评估至关重要.
研究的目的:
- 通过信息敏感度方法优化水质评价指数系统.
- 为了比较优化索引系统与原始系统的准确性.
- 评估水质计算中的效率提升.
主要方法:
- 用于简化水质指数系统的信息敏感度指数选方法.
- 用于比较分析的可变模糊综合评估方法.
- 在郭河的孟门上进行的案例研究.
主要成果:
- 水质评估指数系统从17个指标减少到12个指标,下降了29.41%.
- 优化的索引系统结果显示与原始系统一致,错误率低于10%.
- 孟门的水质被发现稳定在I级水平.
结论:
- 信息敏感度方法有效地减少了指标冗余,同时保留了关键数据.
- 可变模糊综合评估准确地反映了复杂的水质关系.
- 最优化的方法提高了效率,并为河水质量指数的选择提供了科学基础.
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