Swarm Intelligence -

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Résumé :
Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions.
Volume 3 includes 27 chapters presenting real-world applications of swarm intelligence algorithms and related evolutionary algorithms.
With contributions from an international selection of leading researchers, Swarm Intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence.

Sommaire:

• Chapter 1: Prototype generation based on MOPSO
• Chapter 2: Image reconstruction algorithms for electrical impedance tomography based on swarm intelligence
• Chapter 3: A semisupervised fuzzy GrowCut algorithm for segmenting masses of regions of interest of mammography images
• Chapter 4: Multiobjective optimization of autonomous control for a biped robot
• Chapter 5: Swarm intelligence based MIMO detection techniques in wireless systems
• Chapter 6: Swarm intelligence in logistics and production planning
• Chapter 7: Swarm intelligence for object-based image analysis
• Chapter 8: Evolutionary multiobjective optimization for multilabel learning
• Chapter 9: Image segmentation by flocking-like particle dynamics
• Chapter 10: Swarm intelligence for controller tuning and control of fractional systems
• Chapter 11: PSO-based implementation of smart antennas for secure localisation
• Chapter 12: Evolutionary computation for NLP tasks
• Chapter 13: Particle swarm optimisation for antenna element design
• Chapter 14: Swarm intelligence for data mining classification tasks: an experimental study using medical decision problems
• Chapter 15: Towards spiking neural systems synthesis
• Chapter 16: Particle swarm optimization based memetic algorithms framework for scheduling of central planned and distributed flowshops
• Chapter 17: Particle swarm optimization for antenna array synthesis, diagnosis and healing
• Chapter 18: Designing a fuzzy logic controller with particle swarm optimisation algorithm
• Chapter 19: Adding swarm intelligence for slope stability analysis
• Chapter 20: Software module clustering using particle swarm optimization
• Chapter 21: A swarm intelligence approach to harness maximum techno-commercial benefits from smart power grids
• Chapter 22: Fuzzy adaptive tuning of a particle swarm optimization algorithm for variable-strength combinatorial test suite generation
• Chapter 23: Multiobjective swarm optimization for operation planning of electric power systems
• Chapter 24: Perturbed-attractor particle swarm optimization for image restoration
• Chapter 25: Application of swarm intelligence algorithms to multi-objective distributed local area network topology design problem
• Chapter 26: Swarm intelligence algorithms for antenna design and wireless communications
• Chapter 27: Finite-element model updating using swarm intelligence algorithms