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Strategies for Parallelizing Swarm Intelligence Algorithms
2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2015--
Cicirelli Franco +5 more
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Overview of Algorithms for Swarm Intelligence
2011Swarm intelligence (SI) is based on collective behavior of selforganized systems. Typical swarm intelligence schemes include Particle Swarm Optimization (PSO), Ant Colony System (ACS), Stochastic Diffusion Search (SDS), Bacteria Foraging (BF), the Artificial Bee Colony (ABC), and so on. Besides the applications to conventional optimization problems, SI
Shu-Chuan Chu 0001 +3 more
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Swarm Intelligence Algorithms for Portfolio Optimization
2010Swarm Intelligence (SI) is a relatively new technology that takes its inspiration from the behavior of social insects and flocking animals In this paper, we focus on two main SI algorithms: Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) An extension of ACO algorithm and a PSO algorithm has been implemented to solve the portfolio ...
Hanhong Zhu, Yun Chen, Kesheng Wang
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A Swarm Intelligence Algorithm Inspired by Twitter
2016For many years, evolutionary computation researchers have been trying to extract the swarm intelligence from biological systems in nature. Series of algorithms proposed by imitating animals’ behaviours have established themselves as effective means for solving optimization problems.
Zhihui Lv +3 more
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Developmental Swarm Intelligence
International Journal of Swarm Intelligence Research, 2014In this paper, the necessity of having developmental learning embedded in a swarm intelligence algorithm is confirmed by briefly considering brain evolution, brain development, brainstorming process, etc. Several swarm intelligence algorithms are looked at from developmental learning perspective.
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In-Depth Insights into Swarm Intelligence Algorithms Performance
2021Solving hard optimization problems is one of the most important research topics due to the countless applications in different areas. Since solving such problems is of great importance, numerous metaheuristics were developed, many of which belong to the group of swarm intelligence optimization algorithms.
Eva Tuba, Peter Korosec, Tome Eftimov
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Prospecting Swarm Intelligent Algorithms
2011As reviewed in previous chapters, there are only a few optimization algorithms inspired by animal behavior, including ACO, PSO and GSO. Although, PSO and GSO both are swarm intelligence (SI) optimization algorithms and draw inspiration from animal social forging behavior, both of them were initially proposed for continuous function optimization ...
Lijuan Li, Feng Liu
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SWARM INTELLIGENCE: PSO ALGORITHM
2022A natural metaphor is a key to solve any complex optimization problem in scientific community. [1]The classical optimization problem is unable to solve the highly non linear problem because of non-adaptability. A flexible and adaptable algorithm is needed to model the real-time problem easily. More nature inspired algorithms were emerged.
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A DSL for Swarm Intelligence Algorithms.
We propose a domain-specific language to simplify the expression of Swarm Intelligence algorithms. These algorithms are typically introduced through metaphors, requiring practitioners to manually translate them into low-level implementations.This process can obscure intent and hinder reproducibility.Martins, Kevin, Mendes, Rui
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An intelligent swarm clustering algorithm using swarm similarity measure
2016 16th International Symposium on Communications and Information Technologies (ISCIT), 2016Using big data analysis technologies to cluster user data and mine the potential of stock users is of great significance to telecom operators. In this paper, we present an intelligent swarm clustering algorithm using swarm similarity measure for this purpose.
Baisong Ren +5 more
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