A New Method for Fastening the Convergence of Immune Algorithms Using an Adaptive Mutation Approach

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Journal of Signal and Information Processing

ISSN Print: 2159-4465
ISSN Online: 2159-4481

Website: https://www.scirp.org/journal/jsip
E-mail: jsip@scirp.org

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Submission

"A New Method for Fastening the Convergence of Immune Algorithms Using an Adaptive Mutation Approach"
written by Mohammed Abo-Zahhad, Sabah M. Ahmed, Nabil Sabor, Ahmad F. Al-Ajlouni,
published by Journal of Signal and Information Processing, Vol.3 No.1, 2012

has been cited by the following article(s):

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[1]	Artificial immune algorithm convergence rate estimation based on stochastic process theory 2018 Chinese Control And Decision Conference (CCDC), 2018 DOI:10.1109/CCDC.2018.8407456

[2]	Average convergence rate estimation of clonal selection algorithm Advances in Mechanical Engineering, 2017 DOI:10.1177/1687814017721857

[3]	Using adaptive mutation to accelerate the convergence of immune algorithms for prediction of 3D molecular structure International Journal of Computers and Applications, 2015 DOI:10.1080/1206212X.2016.1188568

[4]	A new convergence rate estimation of general artificial immune algorithm Journal of Intelligent & Fuzzy Systems, 2015 DOI:10.3233/IFS-151559

[5]	Mobile Sink-Based Adaptive Immune Energy-Efficient Clustering Protocol for Improving the Lifetime and Stability Period of Wireless Sensor Networks IEEE Sensors Journal, 2015 DOI:10.1109/JSEN.2015.2424296