Identification Method of Hole Boundary Nodes in a Sustainable Service Manufacturing Network

Authors

  • Ziping Du Information Engineering College, Suzhou Industrial Park Institute Services Outsourcing, Suzhou 215123, China

Abstract

The traditional identification method of hole boundary nodes in the sustainable service manufacturing network encounters redundant nodes repeatedly,
this has the issues of low identification accuracy, poor generalization ability, large positioning error, high error detection rate and large energy
consumption. Therefore, a new method of identifying the hole boundary nodes in a sustainable service manufacturing network is required. Based
on the analysis of the user subnet, service provider subnet and product manufacturer subnet, a super network model of sustainable service-oriented
manufacturing is constructed. According to the network model, the hole of the sustainable service manufacturing network is detected. The location
algorithm, based on distance measurement, is used to locate the nodes in the hole, and the initial boundary triangle plane recursive expansion
algorithm is used to identify the boundary nodes in the positioning nodes, so as to complete the research on the identification method of the hole
boundary nodes in the sustainable service manufacturing network. Compared with the traditional method, the results show that the error of the
proposed method is significantly smaller, and it has a higher recognition accuracy, reduces the energy consumption of the hole boundary nodes in the
sustainable service-oriented manufacturing network, reduces the error detection rate, improves the generalization ability, and has good practicability.

Keywords: Sustainable; Service oriented manufacturing network; Network hole; Boundary nodes; Identification method.

Cite As

Z. Du, "Identification Method of Hole Boundary Nodes in a Sustainable Service Manufacturing Network",
Engineering Intelligent Systems, vol. 29 no. 1, pp. 33-43, 2021.

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Published

2021-01-01

Issue

Vol. 29 No. 1 (2021): International Journal of Engineering Intelligent Systems

Section

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