The monitoring and research of unstable locations in eco-industrial networks. (March 2017)

• Record Type: Journal Article
• Authors: Xiao, Zhongdong; Cao, Binbin; Zhou, Guanghui; Sun, Jianan
• Is Part Of: Computers & industrial engineering. Volume 105(2017)
• Page Start: 234
• Page End: 246
• Publication Date: 2017-03
• Subjects: Eco-industrial network -- Unstable sources -- SDG model -- Community structure -- Detection; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.01.011
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Partitioning community firstly and then detecting unstable sources are adopted. The eco-industrial network has clear community structure. The core nodes and border bridge nodes are all important monitoring nodes. The different community structures can display different industry types. Abstract: A functioning eco-industrial system is a common complex network that often appears to be an unstable phenomenon. The Signed Directed Graph (SDG) model for detecting unstable sources in an eco-industrial network was built based on fault diagnosis technology for the complex system. A method that partitions the community structure of the network firstly and then detects unstable sources with the community was proposed in this paper based on the observed results. In order to clarify the degree of an eco-industrial network detection and undetermined node symbols, the technique based on Principal Component Analysis (PCA) to detect unstable sources and entropy theory for determining the relationships between node enterprises were presented, and we also explored the unstable node enterprises in the eco-industrial network. The Yushen Eco-industrial Park in China was presented as a case for unstable sources analysis. This choice is consistent with the proposed model.