用时间延迟识别布尔控制网络的识别
Tiantian Mu1, Jun-E Feng1, Biao Wang2
1School of Mathematics, Shandong University, No. 27 Shanda South Road, Jinan, PR China.
ISA transactions
|October 21, 2023
概括
本研究介绍了使用Cheng产品识别时间延迟布尔网络 (TBN) 和时间延迟布尔控制网络 (TBCN) 的方法. 介绍了算法来确定网络参数和结构,增强系统分析.
科学领域:
- 系统生物学 系统生物学
- 控制理论 控制理论
- 网络科学 网络科学
背景情况:
- 布尔网络 (BNs) 被广泛用于模拟复杂的生物系统.
- 时间延迟布尔网络 (TBNs) 和时间延迟布尔控制网络 (TBCNs) 引入了对准确建模至关重要的时间动态.
- 从输入输出数据中识别这些网络的结构和参数对于理解系统行为至关重要.
研究的目的:
- 开发用于识别时间延迟布尔网络 (TBNs) 和时间延迟布尔控制网络 (TBCNs) 的新方法.
- 建立基于系统可观测性的TBNs和TBCNs的识别标准.
- 介绍选择延迟参数和重建这些网络的内部结构的算法.
主要方法:
- 使用成产品进行网络分析.
- 根据允许的输入-输出序列来定义可识别性.
- 设计延迟参数选择和子系统分解的算法.
- 应用可观察性标准来进行结构性识别.
主要成果:
- 为TBNs和TBCNs提供了可识别性的正式定义.
- 开发了两个算法来选择适当的延迟参数.
- 可识别性标准是使用可观察性概念来推导的.
- 介绍了构建流程,以确定内部网络结构.
结论:
- 提出的方法为识别TBN和TBCN提供了一种可行的方法.
- 开发的算法和标准有助于更深入地了解动态网络属性.
- 插图示例证实了所介绍的识别技术的有效性.
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