Health monitoring method of power supply chain based on R-tree dynamic index algorithm

Abstract In order to discover and manage the risks in the supply chain in time, the entire supply chain is clearly defined, and a health monitoring method for the power grid material supply chain based on the R-tree dynamic index algorithm is constructed. The overall internal supply chain operation structure of the power company is analyzed. The speed histogram is used to divide the speed field corresponding to the index algorithm in order to measure the node speed domain accurately. The rectangular bounding box of the root node is calculated. The internal health data of the power supply chain is identified. The fuzzy clustering operation is used. The original sample size is obtained. The algorithm data is clustered under the action of the index matrix. Bad data is identified in the supply chain. The overlap threshold and the intra-class compact threshold are initialized. The R-tree dynamic index of the optimal clustering is obtained. Quantity output results are generated, and unhealthy data in the material supply chain is classified. The identification and monitoring of unhealthy data in the supply chain are realized. Experiments show that the proposed method can efficiently monitor the risk factors existing in the material supply chain, and the monitoring of supply chain health risks is consistent with the actual occurrence value, the error is small, the method is feasible and effective, and the robustness is good.