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A comprehensive survey: artificial bee colony (ABC) algorithm and applications
Artificial Intelligence Review, 2012 Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced
Dervis Karaboga +2 more
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Co-clustering optimization using Artificial Bee Colony (ABC) algorithm
Applied Soft Computing Journal, 2020Abstract This paper presents an Artificial Bee Colony (ABC) optimization based algorithm for co-clustering of high-dimensional data. The ABC algorithm is used for optimization problems including data clustering. We incorporate aspects of co-clustering by embedding it into the objective function used for clustering by the ABC algorithm.
Syed Fawad Hussain, Masroor Hussain
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A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems
Applied Soft Computing Journal, 2011Abstract: Artificial Bee Colony (ABC) algorithm was firstly proposed for unconstrained optimization problems on where that ABC algorithm showed superior performance. This paper describes a modified ABC algorithm for constrained optimization problems and compares the performance of the modified ABC algorithm against those of state-of-the-art algorithms ...
Dervis Karaboga, Bahriye Akay
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An upgraded artificial bee colony (ABC) algorithm for constrained optimization problems
Journal of Intelligent Manufacturing, 2012Artificial bee colony (ABC) algorithm developed by Karaboga is a nature inspired metaheuristic based on honey bee foraging behavior. It was successfully applied to continuous unconstrained optimization problems and later it was extended to constrained design problems as well.
Ivona Brajevic +2 more
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Modified Artificial Bee Colony (ABC) Algorithm using Dynamic Technique
Asian Journal of Electrical Sciences, 2021The artificial Bee Colony Algorithm is a maximum optimization technique. It has been used in various research papers. In this paper, the dynamic technique has been used in Artificial Bee Colony Algorithm, before this algorithm used the greedy technology of the algorithm.
Mirza Samiulla Beg, Akhilesh A. Waoo
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Artificial neural network synthesis by means of artificial bee colony (ABC) algorithm
2011 IEEE Congress of Evolutionary Computation (CEC), 2011Artificial bee colony (ABC) algorithm has been used in several optimization problems, including the optimization of synaptic weights from an Artificial Neural Network (ANN). However, this is not enough to generate a robust ANN. For that reason, some authors have proposed methodologies based on so-called metaheuristics that automatically allow designing
Beatriz A. Garro +2 more
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An Artificial Bee Colony (ABC) Algorithm for Efficient Partitioning of Social Networks
International Journal of Intelligent Information Technologies, 2014Social networks clustering is an NP-hard problem because it is difficult to find the communities in a reasonable time; therefore, the solutions are based on heuristics. Social networks clustering aims to collect people with common interest in one group. Several approaches have been developed for clustering social networks. In this paper the researchers,
Amal M. Abu Naser, Sawsan Alshattnawi
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Crop Classification Using Artificial Bee Colony (ABC) Algorithm
2016Identifying which crop is growing in certain areas is important to many national and multinational agricultural agencies for forecasting grain supplies, monitoring farming activity, facilitating crop rotation records, etc. In order to achieve that, the agencies require to schedule censuses on a regular basis.
Roberto Antonio Vázquez +1 more
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Artificial Bee Colony (ABC) Algorithm on Training Artificial Neural Networks
2007 IEEE 15th Signal Processing and Communications Applications, 2007In this work, performance of the artificial bee colony algorithm, a recently proposed algorithm, has been tested on training on artificial neural networks which are widely used in signal processing applications and the performance of the algorithm has been compared to differential evolution and particle swarm optimization algorithms which are also ...
Dervis Karaboga, Bahriye Akay
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Overview of Artificial Bee Colony (ABC) algorithm and its applications
2012 IEEE International Systems Conference SysCon 2012, 2012Real-world optimization problems are very difficult and have high degrees of uncertainty. Conventional optimization algorithms have some limitations (i.e., local solution attainment and/or divergence) in solving such problems. On the other hand, meta-heuristic algorithms prove to be competent in outperforming deterministic algorithms, especially when ...
Fahad S. Abu-Mouti, Mohamed E. El-Hawary
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