Applied Optimization and Swarm Intelligence / edited by Eneko Osaba, Xin-She Yang.
Contributor(s): Osaba, Eneko, editor literario | Yang, Xin-She., editor literario
Series: (Springer Tracts in Nature-Inspired Computing, 2524-5538); (Intelligent Technologies and Robotics (SpringerNature-42732)); (Intelligent Technologies and Robotics (R0) (SpringerNature-43728)).Publisher: Singapore : Springer International Pulishing, 2021Edition: First edition 2021.Description: 1 recurso en línea (XI, 229 páginas) : 47 ilustraciones, 26 ilustraciones a color.ISBN: 9789811606625.Subject: Optimización matemática
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | Q337.3 2021 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.23122196 |
Applied Optimization and Swarm Intelligence: A Systematic Review and Prospect Opportunities -- A Review on Ensemble Methods and their Applications to Optimization Problems -- A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining -- Review of Swarm Intelligence for Improving Time Series Forecasting -- Soccer-Inspired Metaheuristics: Systematic Review of Recent Research and Applications -- Formal Cognitive Modeling of Swarm Intelligence for Decision-Making Optimization Problems -- Nature-Inspired Optimization Algorithms for Path Planning and Fuzzy Tracking Control of Mobile Robots -- A Hardware Architecture and Physical Prototype for General-Purpose Swarm Minirobotics: Proteus II -- Evolving a Multi-Objective Optimization Framework -- Swarm Intelligence Based Optimum Design of Deep Excavation System.
This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.
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