Method of Multilevel Adaptive Synthesis of Monitoring Object Knowledge Graphs

• Main Authors: Kirill Krinkin, Alexander Vodyaho, Igor Kulikov, Nataly Zhukova
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Applied Sciences
• Subjects: knowledge graph; deductive synthesis; adaptive synthesis; multilevel object model; inductive synthesis; object state prediction
• Online Access: https://www.mdpi.com/2076-3417/11/14/6251

The paper introduces a method for adaptive deductive synthesis of state models, of complex objects, with multilevel variable structures. The method makes it possible to predict the state of objects using the data coming from them. The data from the objects are collected with sensors installed on them. Multilevel knowledge graphs (KG) are used to describe the observed objects. The new adaptive synthesis method develops previously proposed inductive and deductive synthesis methods, allowing the context to be taken into account when predicting the states of the monitored objects based on the data obtained from them. The article proposes the algorithm for the suggested method and presents its computational complexity analysis. The software system, based on the proposed method, and the algorithm for multilevel adaptive synthesis of the object models developed, are described in the article. The effectiveness of the proposed method is shown in the results from modeling the states of telecommunication networks of cable television operators.