Linear approximation fuzzy model for fault detection in cyber-physical system for supply chain management
Liying Wang, Yichao Zhang
Abstract
The paper’s goal is to propose an IoT assisted Cyber-Physical System with a fault detection technique using a fuzzy algorithm for the supply chain management (SCM). Mathematical models are important for detecting faults. Devicescan contribute to device vulnerabilities. Propertiesof the components in an embedded application can identify defective components in cyber systems of SCM. In this paper linear approximation Boolean fuzzifier model can detect faults in cyber systems of SCM. The rough-set approximation principle with the fuzzy membership functions not only eliminates the ambiguity in the detection method, whereas it helps to classify faulty components in IoT assisted Cyber-Physical System.
Topics & Concepts
Cyber-physical systemAmbiguityFault detection and isolationComputer scienceSupply chainSupply chain managementFault managementFuzzy setFuzzy logicFault (geology)Data miningSet (abstract data type)Reliability engineeringArtificial intelligenceEngineeringStructural engineeringProgramming languageNode (physics)Operating systemLawSeismologyActuatorPolitical scienceGeologyFuzzy Logic and Control SystemsAdvanced Data Processing TechniquesCybersecurity and Information Systems