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200415s2020 enk o 001 0 eng d |
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|a YDX
|b eng
|e pn
|c YDX
|d GW5XE
|d OCLCF
|d N$T
|d ESU
|d EBLCP
|d WAU
|d OCLCO
|d OCLCQ
|d OCLCO
|d SFB
|d OCLCQ
|d OCLCO
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| 019 |
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|a 1151191236
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|a 9780128226094
|q (electronic bk.)
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|a 0128226099
|q (electronic bk.)
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|z 9780128197141
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|z 0128197145
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| 035 |
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|a (OCoLC)1150225170
|z (OCoLC)1151191236
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| 050 |
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|a QA76.9.N37
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0 |
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|a 006.3/8
|2 23
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|a Nature-inspired computation and swarm intelligence :
|b algorithms, theory and applications /
|c edited by Xin-She Yang.
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| 260 |
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|a London :
|b Academic Press,
|c 2020.
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| 300 |
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|a 1 online resource
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 500 |
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|a Includes index.
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0 |
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|a Front Cover -- Nature-Inspired Computation and Swarm Intelligence -- Copyright -- Contents -- List of contributors -- About the editor -- Preface -- Acknowledgments -- Part 1 Algorithms -- 1 Nature-inspired computation and swarm intelligence: a state-of-the-art overview -- 1.1 Introduction -- 1.2 Optimization and optimization algorithms -- 1.2.1 Mathematical formulations -- 1.2.2 Gradient-based algorithms -- 1.2.3 Gradient-free algorithms -- 1.3 Nature-inspired algorithms for optimization -- 1.3.1 Genetic algorithms -- 1.3.2 Ant colony optimization -- 1.3.3 Differential evolution
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8 |
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|a 1.3.4 Particle swarm optimization -- 1.3.5 Fire y algorithm -- 1.3.6 Cuckoo search -- 1.3.7 Bat algorithm -- 1.3.8 Flower pollination algorithm -- 1.3.9 Other algorithms -- 1.4 Algorithms and self-organization -- 1.4.1 Algorithmic characteristics -- 1.4.2 Comparison with traditional algorithms -- 1.4.3 Self-organized systems -- 1.5 Open problems for future research -- References -- 2 Bat algorithm and cuckoo search algorithm -- 2.1 Introduction -- 2.2 Bat algorithm -- 2.2.1 Algorithmic equations of BA -- 2.2.2 Pulse emission and loudness -- 2.2.3 Pseudocode and parameters
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| 505 |
8 |
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|a 2.2.4 Demo implementation -- 2.3 Cuckoo search algorithm -- 2.3.1 Cuckoo search -- 2.3.2 Pseudocode and parameters -- 2.3.3 Demo implementation -- 2.4 Discretization and solution representations -- References -- 3 Fire y algorithm and ower pollination algorithm -- 3.1 Introduction -- 3.2 The re y algorithm -- 3.2.1 Algorithmic equations in FA -- 3.2.2 FA pseudocode -- 3.2.3 Scalings and parameters -- 3.2.4 Demo implementation -- 3.2.5 Multiobjective FA -- 3.3 Flower pollination algorithm -- 3.3.1 FPA pseudocode and parameters -- 3.3.2 Demo implementation -- 3.4 Constraint handling
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8 |
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|a 3.5 Applications -- References -- 4 Bio-inspired algorithms: principles, implementation, and applications to wireless communication -- 4.1 Introduction -- 4.2 Selected bio-inspired techniques: principles and implementation -- 4.2.1 Genetic algorithm -- 4.2.2 Differential evolution -- 4.2.3 Particle swarm optimization -- 4.2.4 Bacterial foraging optimization -- 4.3 Application of bio-inspired optimization techniques in wireless communication -- 4.3.1 Bio-inspired techniques for direct modeling application -- 4.3.2 Bio-inspired techniques for inverse modeling application
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|a 4.3.3 Bio-inspired techniques for mobility management in cellular networks -- 4.3.4 Bio-inspired techniques for cognitive radio-based Internet of Things -- 4.4 Conclusion -- References -- Part 2 Theory -- 5 Mathematical foundations for algorithm analysis -- 5.1 Introduction -- 5.2 Optimization and optimality -- 5.3 Norms -- 5.4 Eigenvalues and eigenvectors -- 5.5 Convergence sequences -- 5.6 Series -- 5.7 Computational complexity -- 5.8 Convexity -- References -- 6 Probability theory for analyzing nature-inspired algorithms -- 6.1 Introduction -- 6.2 Random variables and probability
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| 650 |
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0 |
|a Natural computation.
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| 650 |
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0 |
|a Swarm intelligence.
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| 650 |
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6 |
|a Calcul naturel.
|0 (CaQQLa)000265307
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| 650 |
|
7 |
|a Natural computation
|2 fast
|0 (OCoLC)fst01745866
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| 650 |
|
7 |
|a Swarm intelligence
|2 fast
|0 (OCoLC)fst01139953
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| 700 |
1 |
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|a Yang, Xin-She,
|e editor.
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| 776 |
0 |
8 |
|i Print version:
|z 0128197145
|z 9780128197141
|w (OCoLC)1130248742
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| 856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128197141
|z Texto completo
|
