Applied optimization and swarm intelligence / Eneko Osaba, Xin-She Yang, editors.
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 und...
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Full Text (via Springer) |
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| Other Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
Springer,
[2021]
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| Series: | Springer tracts in nature-inspired computing.
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| Subjects: |
MARC
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| 245 | 0 | 0 | |a Applied optimization and swarm intelligence / |c Eneko Osaba, Xin-She Yang, editors. |
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| 505 | 0 | |a 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. | |
| 520 | |a 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. | ||
| 588 | |a Description based upon print version of record. | ||
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| 650 | 7 | |a Swarm intelligence. |2 fast |0 (OCoLC)fst01139953. | |
| 700 | 1 | |a Osaba, Eneko, |e editor. |0 http://id.loc.gov/authorities/names/nb2019008668. | |
| 700 | 1 | |a Yang, Xin-She, |e editor. |0 http://id.loc.gov/authorities/names/nb2006017401 |1 http://isni.org/isni/0000000122821633. | |
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