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对公共卫生紧急情况中的城市协作治理的分析,使用基于BP算法的模糊理论
1School of Management Science and Engineering, Shandong Jianzhu University, Jinan, 250101, China. 13588@sdjzu.edu.cn.
Scientific reports
|December 29, 2024
概括
本研究引入了公共卫生紧急情况 (PHE) 期间城市供应链风险的早期预警系统. 它使用模糊理论和反向传播神经网络 (BPNN) 来改进应急响应和协作治理.
科学领域:
- 供应链管理 供应链管理
- 公共卫生紧急情况 公共卫生紧急情况
- 人工智能的人工智能
背景情况:
- 在公共卫生紧急情况 (PHE) 期间,城市供应链面临重大风险.
- 有效的协作治理对于管理这些供应链中断至关重要.
- 现有的预警系统缺乏动态风险评估所需的精度.
研究的目的:
- 开发一个完整的早期预警机制,用于在PHEs期间对城市供应链风险进行预警.
- 通过改进供应链管理,加强协作治理.
- 利用模糊理论和逆向传播神经网络 (BPNN) 进行准确的风险预测.
主要方法:
- 模糊理论与反向传播神经网络 (BPNN) 算法的集成.
- 使用Matlab软件模拟供应链风险.
- 采用模糊推理技术和神经网络自适应数据建模用于培训和测试.
主要成果:
- 拟议的模型有效地识别了导致供应链恶化的因素,警告误差低 (0.001).
- 在需求预测的准确性和及时性方面取得了显著的改进.
- BPNN算法实现了动态优化和精确的调度,解决了需求高峰和资源分配挑战.
结论:
- 开发的机制准确地及时识别PHEs期间的不利供应链趋势.
- 提高城市应急响应和风险减轻的效率和灵活性.
- 为城市协作治理和供应链弹性提供了理论和实践贡献.
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