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Modeling Swarm Intelligence Algorithms for CPS Swarms
ACM SIGAda Ada Letters, 2020Swarms of cyber-physical systems (CPSs) have a high potential for innovative and successful applications. Swarm intelligence algorithms are one approach to handle the increased complexity that comes with the high number of CPSs in a swarm. In such algorithms, individual CPSs follow simple rules that lead to an emergent behavior.
M. Schranz, M. Sende
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Survey of Swarm Intelligence Algorithms
Proceedings of the 3rd International Conference on Software Engineering and Information Management, 2020Swarm Intelligence (SI) is an AI technique that has the collective behavior of a decentralized, self-organized system. SI has more advantages such as scalability, adaptability, collective robustness and individual simplicity and also has the ability to solve complex problems.
Suganya Selvaraj, Eunmi Choi
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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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SWARM INTELLIGENCE: PSO ALGORITHM
2023A 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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Pneumonia Prediction Using Swarm Intelligence Algorithms
2021In this chapter, a combination of swarm intelligence algorithms is used to diagnose pneumonia from a patient's x-ray report of lungs conditions. The ability of swarm intelligent algorithms to solve a wide range of problems. For the classification of the disease for this research, a feed forward neural network with swarm intelligent algorithms had been ...
R. S. M. Lakshmi Patibandla +3 more
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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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Stagnation analysis of swarm intelligent algorithms
2010 International Conference on Computer Application and System Modeling (ICCASM 2010), 2010The search progress of swarm intelligent algorithms is a kind of complex system evolution. Definitions of pure diversification search and pure intensification search are first given based on detail analysis on search characteristics of swarm intelligent algorithms. Then the pure intensification search is recognized as the essential reason of stagnation
null Junfeng Chen, null Xinnan Fan
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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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Introduction of Swarm Intelligent Algorithms
2011It is fairly accepted fact that one of the most important human activities is decision making. It does not matter what field of activity one belongs to. Whether it is political, military, economic or technological, decisions have a far reaching influence on our lives. Optimization techniques play an important role in structural design, the very purpose
Lijuan Li, Feng Liu
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ELA: A new swarm intelligence algorithm
2014 IEEE International Conference on Progress in Informatics and Computing, 2014By analyzing the living behaviors of eels, this paper proposes a new eel swarm intelligence algorithm. This paper first describes the behavior of migratory eels, extracts three important behaviors-density adaption, neighboring learning and sex mutation, and establishes a model for the mathematical description of the three important behaviors.
Yaosheng Sun, Zhangcan Huang, Yu Chen
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