Modified Danger Theory based optimized artificial immune network on resiliency in cyber-physical system

Resiliency plays major role in developing reliable and robustness in cyber-physical system where the environment is diverse in nature. The cyber-physical system is model with Multi Agent Paradigm and biological inspired Danger Theory based-modified Artificial Immune Network Algorithm demonstrates on resiliency development. The propose algorithm defines resiliency as state awareness and healing process, with dendritic cells as Threshold-based agent population concentration and Artificial Recognization Ball as memory agent correspondingly. This algorithm is validated with simulation results as well numerical analyses.

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