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Artificial Immune Systems: A New Computational Intelligence Approach
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TLDR
The AIS in Context with Other Computational Intelligence Paradigms and Case Studies shows how the immune system in context with other biological systems and other paradigms has changed since the 1970s.Abstract:
Introduction.- Fundamentals of the Immune System.- A Framework for Engineering Artificial Immune Systems.- A Survey of Artificial Immune Systems.- The Immune System in Context with Other Biological Systems.- AIS in Context with Other Computational Intelligence Paradigms.- Case Studies.- Conclusions and Future Trends.- References.- Appendix I: Glossary of Biological Terms.- Appendix II: Pseudocode for Immune Algorithms.- Appendix III: WEB Resources on Artificial Immune Systems. Index.read more
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Learning and optimization using the clonal selection principle
L.N. de Castro,F.J. Von Zuben +1 more
TL;DR: This paper proposes a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune response and derives two versions of the algorithm, derived primarily to perform machine learning and pattern recognition tasks.
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A survey on optimization metaheuristics
TL;DR: The components and concepts that are used in various metaheuristics are outlined in order to analyze their similarities and differences and the classification adopted in this paper differentiates between single solution based metaheURistics and population based meta heuristics.
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Solving Multiobjective Optimization Problems Using an Artificial Immune System
TL;DR: An algorithm based on the clonal selection principle to solve multiobjective optimization problems (either constrained or unconstrained) using Pareto dominance and feasibility to identify solutions that deserve to be cloned and uses two types of mutation.
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Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
TL;DR: An extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in WSNs is presented and a comparative guide is provided to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.
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Humans and Nature: How Knowing and Experiencing Nature Affect Well-Being
Roly Russell,Anne D. Guerry,Patricia Balvanera,Rachelle K. Gould,Xavier Basurto,Kai M. A. Chan,Sarah C. Klain,Jordan Levine,Jordan Tam +8 more
TL;DR: This synthesize multidisciplinary peer-reviewed research on contributions of nature or ecosystems to human well-being mediated through nontangible connections (such as culture) found enormous variation in the methods used, quantity of research, and generalizability of the literature.