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Springer Handbook of Computational Intelligence

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Cover of 'Springer Handbook of Computational Intelligence'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction
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    Chapter 2 Many-Valued and Fuzzy Logics
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    Chapter 3 Possibility Theory and Its Applications: Where Do We Stand?
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    Chapter 4 Aggregation Functions on [0,1]
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    Chapter 5 Monotone Measures-Based Integrals
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    Chapter 6 The Origin of Fuzzy Extensions
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    Chapter 7 F-Transform
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    Chapter 8 Fuzzy Linear Programming and Duality
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    Chapter 9 Basic Solutions of Fuzzy Coalitional Games
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    Chapter 10 Basics of Fuzzy Sets
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    Chapter 11 Fuzzy Relations: Past, Present, and Future
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    Chapter 12 Fuzzy Implications: Past, Present, and Future
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    Chapter 13 Fuzzy Rule-Based Systems
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    Chapter 14 Interpretability of Fuzzy Systems: Current Research Trends and Prospects
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    Chapter 15 Fuzzy Clustering – Basic Ideas and Overview
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    Chapter 16 An Algebraic Model of Reasoning to Support Zadeh’s CWW
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    Chapter 17 Fuzzy Control
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    Chapter 18 Interval Type-2 Fuzzy PID Controllers
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    Chapter 19 Soft Computing in Database and Information Management
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    Chapter 20 Application of Fuzzy Techniques to Autonomous Robots
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    Chapter 21 Foundations of Rough Sets
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    Chapter 22 Rough Set Methodology for Decision Aiding
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    Chapter 23 Rule Induction from Rough Approximations
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    Chapter 24 Probabilistic Rough Sets
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    Chapter 25 Generalized Rough Sets
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    Chapter 26 Fuzzy-Rough Hybridization
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    Chapter 27 Artificial Neural Network Models
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    Chapter 28 Deep and Modular Neural Networks
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    Chapter 29 Machine Learning
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    Chapter 30 Theoretical Methods in Machine Learning
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    Chapter 31 Probabilistic Modeling in Machine Learning
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    Chapter 32 Kernel Methods
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    Chapter 33 Neurodynamics
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    Chapter 34 Computational Neuroscience – Biophysical Modeling of Neural Systems
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    Chapter 35 Computational Models of Cognitive and Motor Control
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    Chapter 36 Cognitive Architectures and Agents
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    Chapter 37 Embodied Intelligence
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    Chapter 38 Neuromorphic Engineering
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    Chapter 39 Neuroengineering
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    Chapter 40 Evolving Connectionist Systems: From Neuro-Fuzzy-, to Spiking- and Neuro-Genetic
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    Chapter 41 Machine Learning Applications
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    Chapter 42 Genetic Algorithms
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    Chapter 43 Genetic Programming
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    Chapter 44 Evolution Strategies
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    Chapter 45 Estimation of Distribution Algorithms
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    Chapter 46 Parallel Evolutionary Algorithms
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    Chapter 47 Learning Classifier Systems
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    Chapter 48 Indicator-Based Selection
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    Chapter 49 Multi-Objective Evolutionary Algorithms
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    Chapter 50 Parallel Multiobjective Evolutionary Algorithms
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    Chapter 51 Many-Objective Problems: Challenges and Methods
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    Chapter 52 Memetic and Hybrid Evolutionary Algorithms
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    Chapter 53 Design of Representations and Search Operators
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    Chapter 54 Stochastic Local Search Algorithms: An Overview
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    Chapter 55 Parallel Evolutionary Combinatorial Optimization
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    Chapter 56 How to Create Generalizable Results
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    Chapter 57 Computational Intelligence in Industrial Applications
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    Chapter 58 Solving Phase Equilibrium Problems by Means of Avoidance-Based Multiobjectivization
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    Chapter 59 Modeling and Optimization of Machining Problems
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    Chapter 60 Aerodynamic Design with Physics-Based Surrogates
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    Chapter 61 Knowledge Discovery in Bioinformatics
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    Chapter 62 Integration of Metaheuristics and Constraint Programming
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    Chapter 63 Graph Coloring and Recombination
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    Chapter 64 Metaheuristic Algorithms and Tree Decomposition
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    Chapter 65 Evolutionary Computation and Constraint Satisfaction
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    Chapter 66 Swarm Intelligence in Optimization and Robotics
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    Chapter 67 Preference-Based Multiobjective Particle Swarm Optimization for Airfoil Design
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    Chapter 68 Ant Colony Optimization for the Minimum-Weight Rooted Arborescence Problem
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    Chapter 69 An Intelligent Swarm of Markovian Agents
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    Chapter 70 Honey Bee Social Foraging Algorithm for Resource Allocation
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    Chapter 71 Fundamental Collective Behaviors in Swarm Robotics
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    Chapter 72 Collective Manipulation and Construction
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    Chapter 73 Reconfigurable Robots
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    Chapter 74 Probabilistic Modeling of Swarming Systems
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    Chapter 75 A Robust Evolving Cloud-Based Controller
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    Chapter 76 Evolving Embedded Fuzzy Controllers
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    Chapter 77 Multiobjective Genetic Fuzzy Systems
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    Chapter 78 Bio-Inspired Optimization of Type-2 Fuzzy Controllers
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    Chapter 79 Pattern Recognition with Modular Neural Networks and Type-2 Fuzzy Logic
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    Chapter 80 Fuzzy Controllers for Autonomous Mobile Robots
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    Chapter 81 Bio-Inspired Optimization Methods
Overall attention for this book and its chapters
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Citations

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Title
Springer Handbook of Computational Intelligence
Published by
Springer-Verlag Berlin Heidelberg, January 2015
DOI 10.1007/978-3-662-43505-2
ISBNs
978-3-66-243504-5, 978-3-66-243505-2
Authors

Blum, Christian, Groß, Roderich, De Tré, Guy, Zadrozny, Slawomir

Editors

Janusz Kacprzyk, Witold Pedrycz

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 136 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 18%
Student > Master 17 13%
Student > Doctoral Student 11 8%
Researcher 9 7%
Student > Bachelor 6 4%
Other 15 11%
Unknown 53 39%
Readers by discipline Count As %
Engineering 33 24%
Computer Science 23 17%
Materials Science 3 2%
Business, Management and Accounting 2 1%
Mathematics 2 1%
Other 13 10%
Unknown 60 44%