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 1 contains 20 chapters presenting the basic principles and current algorithms and methods of well-known swarm intelligence algorithms and efficient improvements from typical particle swarm optimization (PSO), ant colony optimization (ACO) and fireworks algorithm (FWA) as well as other swarm intelligence algorithms for swarm robotics.
Volume 2 includes 17 chapters covering front-edge research with novel and newly proposed algorithms and methods.
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.
Reihe
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Maße
Höhe: 234 mm
Breite: 156 mm
ISBN-13
978-1-78561-633-4 (9781785616334)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Klassifikation
Ying Tan is a full professor, PhD advisor, and director of the Computational Intelligence Laboratory at Peking University, China. He is also a professor at the Faculty of Design, Kyushu University, Japan. He serves as Editor-in-Chief of the International Journal of Computational Intelligence and Pattern Recognition (IJCIPR), and is Associate Editor of IEEE Transactions on Evolutionary Computation (TEC), IEEE Transactions on Cybernetics (CYB), IEEE Transactions on Neural Networks and Learning Systems (NNLS), International Journal of Swarm Intelligence Research (IJSIR), and International Journal of Artificial Intelligence (IJAI). He has been the founder general chair of the ICSI International Conference series since 2010, is the inventor of the Fireworks Algorithm (FWA), and has published extensively in this field.
Herausgeber*in
ProfessorPeking University, Computational Intelligence Laboratory, China
Volume 1
Chapter 1: Survey of swarm intelligence
Chapter 2: Generalization ability of swarm intelligence algorithms
Chapter 3: A unifying framework for swarm intelligence-based hybrid algorithms
Chapter 4: Ant colony systems for optimization problems in dynamic environments
Chapter 5: Ant colony optimization for dynamic combinatorial optimization problems
Chapter 6: Comparison of multidimensional swarm embedding techniques by potential fields
Chapter 7: Inertia weight control strategies for PSO algorithms
Chapter 8: Robot path planning using swarms of active particles
Chapter 9: MAHM: a PSO-based multiagent architecture for hybridisation of metaheuristics
Chapter 10: The critical state in particle swarm optimisation
Chapter 11: Bounded distributed flocking control of nonholonomic mobile robots
Chapter 12: Swarming in forestry environments: collective exploration and network deployment
Chapter 13: Guiding swarm behavior by soft control
Chapter 14: Agreeing to disagree: synergies between particle swarm optimisation and complex networks
Chapter 15: Ant colony algorithms for the travelling salesman problem and the quadratic assignment problem
Chapter 16: A review of particle swarm optimization for multimodal problems
Chapter 17: Decentralized control in robotic swarms
Chapter 18: PSO in ANN, SVM and data clustering
Chapter 19: Modelling of interaction in swarm intelligence focused on particle swarm optimization and social networks optimization
Chapter 20: Coordinating swarms of microscopic agents to assemble complex structures
Volume 2
Chapter 1: Standard fireworks algorithm 2017
Chapter 2: Guided fireworks algorithm applied to multilevel image thresholding
Chapter 3: Credit card number encryption using firework-based key generation
Chapter 4: ST (Shafiabady-Teshnehlab) optimization algorithm
Chapter 5: Predator-prey optimization with heterogeneous swarms
Chapter 6: A novel modified ant lion optimizer algorithm: extension to proposed 4D-TC
Chapter 7: Push-pull glowworm swarm optimization algorithm for multimodal functions
Chapter 8: Firefly algorithm and its applications
Chapter 9: The optimization dialectical method for the multiple sequences alignment problem
Chapter 10: A new binary moth-flame optimization algorithm (BMFOA) - development and application to solve unit commitment problem
Chapter 11: Binary whale optimization algorithm for unit commitment problem in power system operation
Chapter 12: Real-coded grey wolf optimisation algorithm for progressive thermal power system unit commitment
Chapter 13: Application of grey wolf optimization in fuzzy controller tuning for servo systems
Chapter 14: Smart swarm inspired algorithms for microwave imaging problems
Chapter 15: Interactive chaotic evolution
Chapter 16: Symbiotic organisms search algorithm for static and dynamic transmission expansion planning
Chapter 17: Inclined planes system optimisation (IPO) and its applications in data mining and system identification
Volume 3
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
