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Artificial Immune Systems

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Cover of 'Artificial Immune Systems'

Table of Contents

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    Book Overview
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    Chapter 1 A Gradient-Based Artificial Immune System Applied to Optimal Power Flow Problems
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    Chapter 2 Multimodal Dynamic Optimization: From Evolutionary Algorithms to Artificial Immune Systems
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    Chapter 3 NAIS: A Calibrated Immune Inspired Algorithm to Solve Binary Constraint Satisfaction Problems
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    Chapter 4 A Solution Concept for Artificial Immune Networks: A Coevolutionary Perspective
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    Chapter 5 Artificial Immune Systems for Classification of Petroleum Well Drilling Operations
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    Chapter 6 The SUPRAIC Algorithm: A Suppression Immune Based Mechanism to Find a Representative Training Set in Data Classification Tasks
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    Chapter 7 The Influence of Diversity in an Immune–Based Algorithm to Train MLP Networks
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    Chapter 8 Applying Biclustering to Text Mining: An Immune-Inspired Approach
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    Chapter 9 Defence Against 802.11 DoS Attacks Using Artificial Immune System
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    Chapter 10 A Novel Immune Inspired Approach to Fault Detection
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    Chapter 11 Towards a Novel Immune Inspired Approach to Temporal Anomaly Detection
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    Chapter 12 Bankruptcy Prediction Using Artificial Immune Systems
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    Chapter 13 Phase Transition and the Computational Complexity of Generating r-Contiguous Detectors
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    Chapter 14 Real-Valued Negative Selection Algorithm with a Quasi-Monte Carlo Genetic Detector Generation
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    Chapter 15 A Novel Fast Negative Selection Algorithm Enhanced by State Graphs
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    Chapter 16 Clonal Selection Algorithms for 6-DOF PID Control of Autonomous Underwater Vehicles
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    Chapter 17 An Immuno Robotic System for Humanitarian Search and Rescue (Application Stream)
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    Chapter 18 The Application of a Dendritic Cell Algorithm to a Robotic Classifier
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    Chapter 19 On Immune Inspired Homeostasis for Electronic Systems
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    Chapter 20 Modeling Migration, Compartmentalization and Exit of Naive T Cells in Lymph Nodes Without Chemotaxis
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    Chapter 21 Revisiting the Central and Peripheral Immune System
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    Chapter 22 Topological Constraints in the Evolution of Idiotypic Networks
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    Chapter 23 A Computational Model for the Cognitive Immune System Theory Based on Learning Classifier Systems
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    Chapter 24 Motif Detection Inspired by Immune Memory
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    Chapter 25 An Immune-Inspired Approach to Speckled Computing
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    Chapter 26 Biological Inspiration for Artificial Immune Systems
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    Chapter 27 Regulatory T Cells: Inspiration for Artificial Immune Systems
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    Chapter 28 Automated Blog Design System with a Population-Based Artificial Immune Algorithm
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    Chapter 29 Immune and Evolutionary Approaches to Software Mutation Testing
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    Chapter 30 An Artificial Immune System Based Approach for English Grammar Checking
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    Chapter 31 A Novel Clonal Selection Algorithm Based Fragile Watermarking Method
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    Chapter 32 BeeAIS: Artificial Immune System Security for Nature Inspired, MANET Routing Protocol, BeeAdHoc
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    Chapter 33 A Cultural Immune System for Economic Load Dispatch with Non-smooth Cost Functions
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    Chapter 34 Artificial Immune System to Find a Set of k-Spanning Trees with Low Costs and Distinct Topologies
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    Chapter 35 How to Obtain Appropriate Executive Decisions Using Artificial Immunologic Systems
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    Chapter 36 An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions
Attention for Chapter 27: Regulatory T Cells: Inspiration for Artificial Immune Systems
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Chapter title
Regulatory T Cells: Inspiration for Artificial Immune Systems
Chapter number 27
Book title
Artificial Immune Systems
Published in
Lecture notes in computer science, January 2007
DOI 10.1007/978-3-540-73922-7_27
Book ISBNs
978-3-54-073921-0, 978-3-54-073922-7
Authors

T. S. Guzella, T. A. Mota-Santos, W. M. Caminhas

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 25%
Unknown 3 75%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Student > Doctoral Student 1 25%
Student > Master 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Agricultural and Biological Sciences 1 25%
Medicine and Dentistry 1 25%