一个分析层次过程与人工神经网络模型相结合,以评估可持续的污泥处理场景
Yuhan Wu1, Diannan Huang1, Li Zhang1
1School of Municipal and Environmental Engineering, Shenyang Jianzhu University, Shenyang 110168, China.
Waste management (New York, N.Y.)
|April 20, 2025
概括
选择最佳的污泥管理策略对中国至关重要. 一个集成的分析层次过程 (AHP) -人工神经网络 (ANN) 模型有效评估了治疗场景,确定无氧消化是最可持续的选择.
科学领域:
- 环境科学 环境科学
- 工程 工程师 工程师 工程师
- 数据科学数据科学数据科学
背景情况:
- 中国的泥管理面临着重大的环境,经济和技术障碍.
- 由于缺乏全面的研究,需要定量决策工具来选择最佳的管理策略.
研究的目的:
- 开发和验证一个集成的分析层次过程 (AHP) -人工神经网络 (ANN) 模型,用于评估污泥处理场景.
- 为工程优化污泥管理提供量化基础.
主要方法:
- 使用AHP建立了层次评估模型,权重来自专家调查和经验数据.
- 引导方法用于对ANN模型进行强有力的训练,该模型将评估指标映射到预期值.
- 根据碳排放,环境影响和经济成本,评估了四种代表性污泥处理场景.
主要成果:
- AHP-ANN模型显示出高预测准确度,测试数据集的最大平均平方误差 (MSE) 为0.00052.
- 该模型促进了对参数调整的快速评估,并支持工程优化.
- 无氧消化 (S1) 成为表现最好的方案,提供较低的环境影响和运营成本.
- 焚烧 (S3) 由于高资源消耗,环境影响和运营成本,表现最差.
结论:
- 综合AHP-ANN模型是用于定量评估和优化污泥处理策略的强大工具.
- 无氧消化被推为中国最可持续的污泥管理方法,平衡环境和经济因素.
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