The Receptor Density Algorithm

作者：Owens Nick D L^*; Greensted Andrew; Timmis Jon; Tyrrell Andy

来源：Theoretical Computer Science, 2013, 481: 51-73.

DOI：10.1016/j.tcs.2012.10.057

• Bio-inspired algorithms
• Artificial immune systems
• T cell signalling
• Kernel density estimation
• Anomaly detection
• Exponential smoothing
• Weighted moving average
• Recurrent equations

This paper describes the biological and theoretical foundations of a new Artificial Immune System the Receptor Density Algorithm. The algorithm is developed with inspiration from T cell signalling processes and has application in anomaly detection. Connections between the Receptor Density Algorithm and kernel density estimation with exponential smoothing are demonstrated. Finally, the paper evaluates the algorithm%26apos;s performance on two types of anomaly detection problem.

• 出版日期2013-4-15