Recent Advances in Swarm Intelligence Algorithms and Their Applications

This reprint comprises a collection of 20 articles that were accepted and published in the Special Issue titled " Recent Advances in Swarm Intelligence Algorithms and Their Applications" of the MDPI journal Mathematics. These articles cover a wide range of topics related to swarm intellige...

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Bibliographic Details
Other Authors: Dong, Jian (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
HBA
LMS
n/a
Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a This reprint comprises a collection of 20 articles that were accepted and published in the Special Issue titled " Recent Advances in Swarm Intelligence Algorithms and Their Applications" of the MDPI journal Mathematics. These articles cover a wide range of topics related to swarm intelligence algorithms and their theories. The topics include improvements in algorithm mechanisms, fusion algorithms, multiobjective optimization, and the optimization of large-scale problems, as well as the application of swarm intelligence in various fields such as engineering optimization problems, vehicle swarm motion, viscoelastic Maxwell-type DVA, and deep learning. It is hoped that this reprint will be helpful for scholars engaged in the field of swarm intelligence and also suitable for researchers interested in staying updated with the latest advancements in swarm intelligence algorithms and their applications. Nowadays, swarm intelligence is closely intertwined with various aspects of life. This reprint aims to provide readers with an understanding of these developments and further expand the application boundaries of such algorithms. 
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653 |a preference incorporation 
653 |a ant colony optimisation 
653 |a grey wolf optimisation 
653 |a interval outranking 
653 |a multi-criteria decision analysis 
653 |a swarm intelligence algorithms 
653 |a piecewise linearization 
653 |a optimization 
653 |a parameter tuning 
653 |a approximation 
653 |a experimental comparison 
653 |a graph convolutional network 
653 |a relation extraction 
653 |a machine learning 
653 |a natural language processing 
653 |a metaheuristic algorithms 
653 |a Whale Optimization Algorithm 
653 |a HBA 
653 |a radial distribution systems 
653 |a power loss 
653 |a sensitivity analysis 
653 |a DG optimal allocation 
653 |a voltage deviation 
653 |a capacitor banks 
653 |a electricity market 
653 |a optimal bidding 
653 |a Harris Hawk Optimization 
653 |a multi layered neural network 
653 |a bi-level optimization 
653 |a strategic bidding 
653 |a ground-penetrating radar (GPR) 
653 |a cavity morphology recognition 
653 |a few-shot learning (FSL) 
653 |a deep learning (DL) 
653 |a relation network (RelationNet) 
653 |a unmanned aerial vehicle swarm 
653 |a antenna array 
653 |a near-field beamforming 
653 |a array element position error compensation 
653 |a spatial area division 
653 |a economic load dispatch 
653 |a pigeon-inspired optimizer 
653 |a oppositional-based learning 
653 |a swarm intelligence algorithm 
653 |a oppositional-based pigeon-inspired optimizer 
653 |a tunicate swarm algorithm 
653 |a chaotic mapping 
653 |a Lévy flight strategy 
653 |a benchmark test functions 
653 |a engineering design problems 
653 |a meta-heuristic 
653 |a large-scale agents 
653 |a attack and defense 
653 |a multi-population mean-field game 
653 |a high-dimensional solution space 
653 |a neural networks 
653 |a bat algorithm 
653 |a hybrid strategy 
653 |a energy harvesting 
653 |a NOMA 
653 |a cognitive relay network 
653 |a multimodal optimization 
653 |a multiple optima 
653 |a partition-based random search 
653 |a niching 
653 |a global optimization problems 
653 |a moth-flame optimization 
653 |a premature convergence 
653 |a population diversity 
653 |a grey wolf optimization 
653 |a swarm intelligence 
653 |a real world application 
653 |a spiking neural P system 
653 |a AEC system 
653 |a LMS 
653 |a neuromorphic architecture 
653 |a FPGA 
653 |a Harris hawks optimization 
653 |a elite opposition-based learning 
653 |a Sobol sequence 
653 |a nonlinear weight 
653 |a Gaussian walk learning 
653 |a particle swarm optimization algorithm 
653 |a dynamic vibration absorber 
653 |a Maxwell-type 
653 |a inerter 
653 |a negative stiffness 
653 |a chaotic-based PPE algorithm 
653 |a meta-heuristic algorithm 
653 |a chaotic maps 
653 |a Mahjong 
653 |a differential evolution 
653 |a deficiency number 
653 |a combinatorial optimization 
653 |a reinforcement learning 
653 |a multi-agent reinforcement learning 
653 |a self play 
653 |a population play 
653 |a n/a 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/112549  |7 0  |z DOAB: description of the publication