Artificial Immune Systems: A New Computational Intelligence Approach

By Leandro Nunes de Castro, J. Timmis. 2002

1,910 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d250e7ac9ececc1c0d732478c8138d6367400c2a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Solving Multiobjective Optimization Problems Using an Artificial Immune System (2005, methodology): “For this discussion, we used the framework provided in [ 32 ], according to which, an artificial immune system, being a biologically inspired algorithm, requires are least three basic elements:”
Rule extraction from trained adaptive neural networks using artificial immune systems (2009, methodology): “The immune network theory was proposed by Jerne in 1974 (de Castro & Timmis, 2002).”
Optimal power flow: a bibliographic survey II (2012, methodology): “AIS clonal rate, mutation rate, matching number – [39] EA; learning algorithm; promising for security applications in OPF and in hybrid methods for OPF”
Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm (2004, methodology): “Work in [9] adopted the term shape-space to describe the shape of the data being used, and defined a number of affinity measures, such as Euclidean distance, which can be used to determine the interaction between elements in the AIS.”
A review of machine learning approaches to Spam filtering (2009, background): “Oda and White (2003a) proposed an Artificial Immune System (see, e.g., de Castro & Timmis, 2002) for Spam filtering, where detectors, represented as regular expressions, are used for pattern matching in a message being analyzed.”
Multiobjective Optimization Using Ideas from the Clonal Selection Principle (2003, background): “For functions and , variable is defined over the range [0, 1], and, in the case of function , the variables and are defined over the range .”
Biogeography-Based Optimization for Different Economic Load Dispatch Problems (2010, background): “3) BBO involves fewer computational steps per iteration compared to AIS.”
A comprehensive survey on network anomaly detection (2018, background): “Artificial Immune Systems (AIS) are adaptive systems, enhanced by theoretical immunology and biological immune system functions, principles and models, and are applied to problem-solving, as defined by de Castro and Timmis [139].”
Immune system approaches to intrusion detection – a review (2004, background): “Keywords artificial immune systems, intrusion detection systems, literature review”
Fundamentals of natural computing: an overview (2007, background): “Five main types of algorithms are available in the literature: • Bone marrow: used to generate populations of immune cells and molecules to be used in AIS and possibly in other approaches, such as genetic algorithms (e.g., [137,212,226]).”