在能源成本降低中检测最小的扩展驱动节点
Bingbo Wang1, Jiaojiao He1, Qingdou Meng1
1School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
Chaos (Woodbury, N.Y.)
|August 15, 2024
概括
在复杂网络中,通过识别最小扩展驱动节点 (MIER) 来实现控制能量的最小化. 这种方法可以显著降低生物,社会和神经系统的能源成本.
科学领域:
- 复杂系统科学 复杂系统科学
- 网络理论 网络理论
- 系统生物学 系统生物学
背景情况:
- 复杂网络中的节点状态和连接性决定了系统动态和控制成本.
- 使用最小的输入节点最小化控制能量是网络科学中一个关键的,但尚未解决的问题.
研究的目的:
- 调查复杂的网络结构,特别是封闭连接的功能模块和控制能源之间的联系.
- 提出并验证一种新的方法,即能源成本降低 (MIER) 中最小扩展驱动节点,以减少控制能量.
主要方法:
- 将MIER检测转化为一个多目标优化问题.
- 采用NSGA-II算法来近似MIER的最佳解决方案.
- 使用合成和现实世界的网络数据验证了该方法,包括对稳定性的扰动测试.
主要成果:
- MIER显著降低了控制能量,降低通常是指数的.
- 微小的结构修改,比如添加扩展的驱动节点,大大降低了能源需求.
- 与基线方法相比,NSGA-II有效地接近最佳解决方案.
结论:
- 在复杂的系统中,MIER提供了一种实用的计算工具,用于降低控制能量.
- 在生物学 (基因调节),经济 (贸易网络) 和神经系统方面,MIER方法得到了成功的应用.
- MIER增强了系统功能,确定了关键节点,并揭示了潜在的监管机制.
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