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Applied Nature-Inspired Computing : Algorithms and Case Studies - Author

Applied Nature-Inspired Computing

Algorithms and Case Studies

By: Author

eText | 10 August 2019

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This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each.

Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.

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Non-FictionEngineering & TechnologyTechnology in GeneralEngineering in GeneralComputing & I.T.Computer ScienceArtificial IntelligenceComputer Programming & Software DevelopmentAlgorithms & Data StructuresDatabasesData Capture & AnalysisGraphical & Digital Media Applications
3D Graphics & ModellingMathematicsApplied MathematicsMathematical Theory of ComputationMaths for Computer Scientists

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