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Training Feed-Forward Artificial Neural Networks with a modified artificial bee colony algorithm
Xu,Feiyi1; Pun,Chi Man2; Li,Haolun3,4; Zhang,Yushu5; Song,Yurong1; Gao,Hao2,3
Source PublicationNeurocomputing

Deep learning is a branch of neural network which has been intensively developed in the last decade. Due to the high-accuracy classification ability, the deep learning algorithms have been widely used in many fields, such as speech recognition, image recognition, and natural speech processing. However, they also show some shortcomings especially on the selection of some parameters in the network, including hyper-parameters, which is still treated as a time consuming task. In this paper, a modified ABC (ABC-ISB) optimization algorithm is proposed to automatically train the parameters of Feed-Forward Artificial Neural Networks, which is a typical a neural network. In the proposed ABC algorithm, we utilize the information of neighbors with better performance to accelerate the convergence of employed and onlooker bees respectively. In addition, a new selection strategy and a gbest-guided strategy are introduced to enhance the global search capability and balance the exploration and exploitation of the algorithm separately. The experimental results show our ABC-ISB is generally leading and competitive.

KeywordArtificial Bee Colony Deep Learning Feed-forward Artificial Neural Networks Parameter Selection
URLView the original
Indexed BySCIE
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000581754500009
Scopus ID2-s2.0-85068265141
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Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Corresponding AuthorSong,Yurong; Gao,Hao
Affiliation1.School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing,China
2.Department of Computer and Information Science,University of Macau,Macao
3.The Institute of Advanced Technology,Nanjing University of Posts and Telecommunications,Nanjing,China
4.Beijing Institute of Control Engineering,China
5.College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing,China
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xu,Feiyi,Pun,Chi Man,Li,Haolun,et al. Training Feed-Forward Artificial Neural Networks with a modified artificial bee colony algorithm[J]. Neurocomputing,2020,416:69-84.
APA Xu,Feiyi,Pun,Chi Man,Li,Haolun,Zhang,Yushu,Song,Yurong,&Gao,Hao.(2020).Training Feed-Forward Artificial Neural Networks with a modified artificial bee colony algorithm.Neurocomputing,416,69-84.
MLA Xu,Feiyi,et al."Training Feed-Forward Artificial Neural Networks with a modified artificial bee colony algorithm".Neurocomputing 416(2020):69-84.
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