Proceedings Article10.1109/ICINIS.2013.38
Ant Colony Clustering Algorithm Based on Swarm Intelligence
Dong Li-yan,Zhang Sainan,Tian Geng,Li Yongli,Cai Guanyan +4 more
- 01 Nov 2013
- pp 123-126
TL;DR: This paper proposes an ant colony clustering algorithm based on swarm intelligence that improved from the method of calculating the similarity measure and enhanced ant memory, and also proposed a new policy of picking and dropping objects, which is picking the objects which have been formation of micro-clustering.
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Abstract: Aim at the clustering result of traditional ant colony clustering algorithm is not accurate and the algorithm operating efficiency lower, many modified algorithm have been proposed. In this paper, we propose an ant colony clustering algorithm based on swarm intelligence. This algorithm not only improved from the method of calculating the similarity measure and enhanced ant memory, and also proposed a new policy of picking and dropping objects, which is picking the objects which have been formation of micro-clustering. Through experiment contrast, this paper presents the ant colony clustering algorithm based on swarm intelligence than the traditional ant colony algorithm in terms of efficiency, the correct rate of the clustering results have significantly improved.
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Citations
Satellite formation keeping via chaotic artificial bee colony
TL;DR: The experimental results indicate the feasibility of the swarm intelligence approach to the problem of estimating optimal feedback control parameter for a pair of satellites in a formation, clearly showing the effective control of the transients that arise because of J2 perturbation.
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Enterprise Workload Management through Ant Colony Optimization
Sami J. Habib,Paulvanna Nayaki Marimuthu,Naser Al-Ibrahim +2 more
- 04 Dec 2014
TL;DR: Re-synthesizing a typical BEN comprising of 100 clients with a heavy traffic into a set of 5 clusters reduces the backbone traffic by 18% and the conversion problem is formulated as an optimization problem with an objective function to maximize the local traffic within the new clusters.
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Automated Robot Communication System Using Swarm Intelligence
Prachi R. Rajarapollu,Debashis Adhikari +1 more
- 30 Jul 2019
TL;DR: The main aim of exploring the concept for the progressive development of swarm robotics in an engineering field and solve the complex real time applications by setting a communication among automated robots.
Influence of Swarm Intelligence in Data Clustering Mechanisms
TL;DR: In this paper , the authors compared the performance of different swarm-based data clustering algorithms such as Artificial Bee Colony Algorithm, Ant Colony Optimization, Firefly Algorithm and Bat Algorithm.
Swarm intelligence for clustering — A systematic review with new perspectives on data mining
Elliackin M. N. Figueiredo,Mariana Macedo,Hugo Siqueira,Clodomir J. Santana,Anu Gokhale,Carmelo J. A. Bastos-Filho +5 more
TL;DR: A systematic mapping review on recent investigations of swarm-inspired algorithms to tackle clustering problems and provides an overview of how to apply the swarm methods together with a critical analysis of the current and future perspectives in the field.
References
Web usage mining using artificial ant colony clustering and linear genetic programming
Ajith Abraham,Vitorino Ramos +1 more
- 08 Dec 2003
TL;DR: An ant clustering algorithm to discover Web usage patterns (data clusters) and a linear genetic programming approach to analyze the visitor trends are proposed and empirical results clearly show that ant colony clustering performs well when compared to a self-organizing map.
Ant-based clustering: a comparative study of its relative performance with respect to k-means, average link and 1d-som
Julia Handl,Joshua Knowles,Marco Dorigo +2 more
- 01 Jan 2003
TL;DR: This work proposes a scheme that enables unbiased interpretation of the clustering solutions obtained, and uses this to conduct a full evaluation of the algorithm, and finds evidence that ant-based clustering is a robust and viable alternative.
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A Stochastic Heuristic for Visualising Graph Clusters in a Bi-DimensionalSpace Prior to Partitioning
TL;DR: A new stochastic heuristic is presented to reveal some structures inherent in large graphs, by displaying spatially separate clusters of highly connected vertex subsets on a two-dimensional grid, inspired by a biological model of ant behavior.
74
Web Usage Mining Using Artificial Ant Colony Clustering and Genetic Programming
Ajith Abraham,Vitorino Ramos +1 more
TL;DR: Wang et al. as mentioned in this paper proposed an ant clustering algorithm to discover Web usage patterns (data clusters) and a linear genetic programming approach to analyze the visitor trends, which clearly shows that ant colony clustering performs well when compared to a self-organizing map (for clustering web usage patterns) even though the performance accuracy is not that efficient when comparared to evolutionary-fuzzy clustering (i-miner) approach.
68
An effective particle swarm optimization method for data clustering.
I.W. Kao,Chi-Yang Tsai,Y.C. Wang +2 more
- 01 Dec 2007
TL;DR: Two reflex schemes are implemented on PSO algorithm to improve the efficiency and their performance is compared with those of PSO, K-means and two other clustering methods.
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