IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Recent Developments In Biologically Inspired Computing
Recent Developments In Biologically Inspired Computing
A novel immune anomaly detection technique based on negative selection
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Structural damage identification based on Bayesian theory and improved immune genetic algorithm
Expert Systems with Applications: An International Journal
A novel chemistry based metaheuristic optimization method for mining of classification rules
Expert Systems with Applications: An International Journal
A transitional view of immune inspired techniques for anomaly detection
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Adaptive fault detection and diagnosis using an evolving fuzzy classifier
Information Sciences: an International Journal
Hi-index | 12.05 |
This paper presents a methodology that enables fault detection in dynamic systems based on recent immune theory. The fault detection is a challenging problem due to increasing complexity of processes and agility necessary to avoid malfunction or accidents. The fault detection central challenge is determining the difference between normal and potential harmful activities at dynamic systems. A promising solution is emerging in the form of Artificial Immune Systems (AIS). The Danger Model (DM) proposes that the immune system reacts not against self or non-self but by threats generated into the organism: the danger signals. DM-based fault detection system proposes a new formulation for a fault detection system. A DM-inspired methodology is applied to a fault detection benchmark provided by DAMADICS to compare its relative performance to others algorithms. The results show that the strategy developed is promising for incipient and abrupt fault detection in dynamic systems.