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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 matemáticaOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
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.
Abstract: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q337.3 2021 EB (Browse shelf(Opens below)) Acceso electrónico eBook.23122196
Total holds: 0

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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