Training Feed-Forward Artificial Neural Networks with a modified artificial bee colony algorithm
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. Howev...
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| Vydáno v: | Neurocomputing (Amsterdam) Ročník 416; s. 69 - 84 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
27.11.2020
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| Témata: | |
| ISSN: | 0925-2312, 1872-8286 |
| On-line přístup: | Získat plný text |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Gao, Hao Song, Yurong Li, Haolun Pun, Chi-Man Xu, Feiyi Zhang, Yushu |
| Author_xml | – sequence: 1 givenname: Feiyi surname: Xu fullname: Xu, Feiyi organization: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China – sequence: 2 givenname: Chi-Man orcidid: 0000-0003-1788-3746 surname: Pun fullname: Pun, Chi-Man organization: Department of Computer and Information Science, University of Macau, Macau – sequence: 3 givenname: Haolun surname: Li fullname: Li, Haolun organization: The Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China – sequence: 4 givenname: Yushu surname: Zhang fullname: Zhang, Yushu organization: College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China – sequence: 5 givenname: Yurong surname: Song fullname: Song, Yurong email: songyr@njupt.edu.cn organization: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China – sequence: 6 givenname: Hao orcidid: 0000-0003-0148-3713 surname: Gao fullname: Gao, Hao email: tsgaohao@gmail.com organization: Department of Computer and Information Science, University of Macau, Macau |
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| Cites_doi | 10.1016/j.knosys.2016.06.014 10.1109/TSMCB.2012.2222373 10.1109/TMAG.2013.2281818 10.1016/S0377-2217(98)00114-3 10.1016/j.asoc.2014.06.035 10.1109/4235.771163 10.1109/5.784219 10.1007/s10462-012-9328-0 10.1016/j.ins.2010.07.015 10.1016/j.asoc.2014.10.020 10.1016/j.knosys.2016.05.052 10.1162/neco.2006.18.7.1527 10.1016/j.ins.2014.12.043 10.1109/TSMC.2014.2351783 10.1016/j.asoc.2012.05.008 10.1016/j.asoc.2015.05.041 10.1016/j.eswa.2014.09.049 10.1016/j.ijepes.2012.04.009 10.1016/j.asoc.2014.11.040 10.1016/j.ins.2014.05.033 10.1109/TNNLS.2014.2342533 10.1038/ncomms5308 10.1109/TCYB.2015.2444383 10.1016/j.ipl.2011.06.002 10.1016/j.asoc.2017.01.031 10.1016/j.asoc.2016.07.039 10.1016/j.ins.2014.10.008 10.1016/j.asoc.2015.12.046 10.1007/s10898-004-9972-2 10.1016/j.knosys.2014.04.042 10.1109/TMAG.2013.2241447 10.1016/j.cor.2011.06.007 10.1109/MSP.2012.2205597 10.1016/S0377-2217(97)00292-0 10.1016/j.ins.2014.10.009 10.1109/TASE.2012.2204874 10.1016/j.ins.2014.12.042 10.1016/j.asoc.2009.12.025 |
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| References | He, Zhang, Ren (bib0003) 2015 Bose, Biswas, Vasilakos (bib0022) 2014; 281 Blum, Socha (bib0047) 2005 Horng (bib0025) 2015; 45 Li, Pan (bib0026) 2015; 316 Sexton, Dorsey, Johnson (bib0049) 1999; 114 Karaboga, Gorkemli (bib0034) 2014; 23 Leung, Yuen, Chow (bib0043) 2012; 12 Kiran, Hakli, Gunduz (bib0036) 2015; 300 Song, Yan, Zhao (bib0051) 2017; 55 Karaboga, Akay, Ozturk (bib0050) 2007 Gao, Liu (bib0030) 2012; 39 Eggensperger, Hutter, Hoos (bib0007) 2015 Gao, Liu, Huang (bib0033) 2013; 43 Li, Yang (bib0037) 2016; 41 Liao, Zhou, Zhang (bib0028) 2012; 43 Ali, Ahn, Pant (bib0016) 2015; 301 Chu, Hu, Niu, Li, Chu (bib0052) 2016 Hinton, Osindero, Teh (bib0001) 2006; 18 Li, Pan, Duan (bib0038) 2016; 46 Karaboga, Gorkemli, Ozturk, Karaboga (bib0013) 2014; 42 Pan, Wang, Mao (bib0027) 2013; 10 Ozturk, Hancer, Karaboga (bib0018) 2015; 28 Bhandari, Kumar, Singh (bib0017) 2015; 42 Zhang, Zhang, Ho (bib0020) 2014; 50 Kuang, Jin, Xu (bib0039) 2014 Hinton (bib0004) 2012; 29 Zhang, Zhang, Yuen (bib0021) 2013; 49 Gu, Sheng, Tay (bib0023) 2015; 26 Akay, Karaboga (bib0031) 2012; 192 Li, Niu, Ma, Wang, Zhang (bib0055) 2014; 67 Karaboga (bib0012) 2005 Sexton, Alidaee, Dorsey (bib0048) 1998; 106 Zhu, Kwong (bib0029) 2010; 217 Yao, Liu, Lin (bib0042) 1999; 3 Yao (bib0046) 1999; 87 Bergstra, Yamins, Cox (bib0011) 2013 Baldi, Sadowski, Whiteson (bib0002) 2014; 5 Gao (bib0056) 2016; 109 Gao, Liu (bib0040) 2011; 111 Karaboga, Kaya (bib0054) 2016; 49 Ilievski, Akhtar, Feng (bib0009) 2017 Habbi, Boudouaoui, Karaboga (bib0024) 2015; 295 Ali, Khompatraporn, Zabinsky (bib0041) 2005; 31 Shi, Pun, Hu, Gao (bib0015) 2016; 107 Karaboga, Ozturk (bib0019) 2011; 11 Bergstra, Bengio (bib0005) 2012; 13 Li, Jamieson, DeSalvo (bib0006) 2017; 18 Babaoglu (bib0032) 2015; 34 Kishan, Mohan, Ranka (bib0045) 1997 Li, Yang, Kıran (bib0053) 2016; 2712-2717 Domhan, Springenberg, Hutter (bib0008) 2015; 15 Kıran, Fındık (bib0035) 2015; 26 Dayhoff (bib0044) 1990 Young, Rose, Karnowski (bib0010) 2015 Karaboga, Akay (bib0014) 2009; 214 Pan (10.1016/j.neucom.2019.04.086_bib0027) 2013; 10 Hinton (10.1016/j.neucom.2019.04.086_bib0001) 2006; 18 Karaboga (10.1016/j.neucom.2019.04.086_bib0012) 2005 Chu (10.1016/j.neucom.2019.04.086_bib0052) 2016 Eggensperger (10.1016/j.neucom.2019.04.086_bib0007) 2015 Karaboga (10.1016/j.neucom.2019.04.086_bib0014) 2009; 214 Kishan (10.1016/j.neucom.2019.04.086_bib0045) 1997 Zhang (10.1016/j.neucom.2019.04.086_bib0020) 2014; 50 Gao (10.1016/j.neucom.2019.04.086_bib0030) 2012; 39 Ilievski (10.1016/j.neucom.2019.04.086_bib0009) 2017 Li (10.1016/j.neucom.2019.04.086_bib0026) 2015; 316 Li (10.1016/j.neucom.2019.04.086_bib0038) 2016; 46 Baldi (10.1016/j.neucom.2019.04.086_bib0002) 2014; 5 Horng (10.1016/j.neucom.2019.04.086_bib0025) 2015; 45 Sexton (10.1016/j.neucom.2019.04.086_bib0049) 1999; 114 Ozturk (10.1016/j.neucom.2019.04.086_bib0018) 2015; 28 Bergstra (10.1016/j.neucom.2019.04.086_bib0011) 2013 Karaboga (10.1016/j.neucom.2019.04.086_bib0019) 2011; 11 Babaoglu (10.1016/j.neucom.2019.04.086_bib0032) 2015; 34 Li (10.1016/j.neucom.2019.04.086_bib0037) 2016; 41 Li (10.1016/j.neucom.2019.04.086_bib0055) 2014; 67 Gu (10.1016/j.neucom.2019.04.086_bib0023) 2015; 26 Sexton (10.1016/j.neucom.2019.04.086_bib0048) 1998; 106 Zhu (10.1016/j.neucom.2019.04.086_bib0029) 2010; 217 Yao (10.1016/j.neucom.2019.04.086_bib0046) 1999; 87 Song (10.1016/j.neucom.2019.04.086_bib0051) 2017; 55 Gao (10.1016/j.neucom.2019.04.086_bib0056) 2016; 109 Ali (10.1016/j.neucom.2019.04.086_bib0041) 2005; 31 Young (10.1016/j.neucom.2019.04.086_bib0010) 2015 Gao (10.1016/j.neucom.2019.04.086_bib0033) 2013; 43 Gao (10.1016/j.neucom.2019.04.086_bib0040) 2011; 111 Blum (10.1016/j.neucom.2019.04.086_bib0047) 2005 Dayhoff (10.1016/j.neucom.2019.04.086_bib0044) 1990 Kuang (10.1016/j.neucom.2019.04.086_bib0039) 2014 Bhandari (10.1016/j.neucom.2019.04.086_bib0017) 2015; 42 Ali (10.1016/j.neucom.2019.04.086_bib0016) 2015; 301 Li (10.1016/j.neucom.2019.04.086_bib0006) 2017; 18 Karaboga (10.1016/j.neucom.2019.04.086_bib0050) 2007 Yao (10.1016/j.neucom.2019.04.086_bib0042) 1999; 3 Karaboga (10.1016/j.neucom.2019.04.086_bib0034) 2014; 23 Habbi (10.1016/j.neucom.2019.04.086_bib0024) 2015; 295 He (10.1016/j.neucom.2019.04.086_bib0003) 2015 Domhan (10.1016/j.neucom.2019.04.086_bib0008) 2015; 15 Karaboga (10.1016/j.neucom.2019.04.086_bib0013) 2014; 42 Kıran (10.1016/j.neucom.2019.04.086_bib0035) 2015; 26 Shi (10.1016/j.neucom.2019.04.086_bib0015) 2016; 107 Leung (10.1016/j.neucom.2019.04.086_bib0043) 2012; 12 Li (10.1016/j.neucom.2019.04.086_bib0053) 2016; 2712-2717 Akay (10.1016/j.neucom.2019.04.086_bib0031) 2012; 192 Hinton (10.1016/j.neucom.2019.04.086_bib0004) 2012; 29 Zhang (10.1016/j.neucom.2019.04.086_bib0021) 2013; 49 Bose (10.1016/j.neucom.2019.04.086_bib0022) 2014; 281 Liao (10.1016/j.neucom.2019.04.086_bib0028) 2012; 43 Kiran (10.1016/j.neucom.2019.04.086_bib0036) 2015; 300 Karaboga (10.1016/j.neucom.2019.04.086_bib0054) 2016; 49 Bergstra (10.1016/j.neucom.2019.04.086_bib0005) 2012; 13 |
| References_xml | – volume: 31 start-page: 635 year: 2005 end-page: 672 ident: bib0041 article-title: A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems publication-title: J. Glob. Optim. – volume: 316 start-page: 487 year: 2015 end-page: 502 ident: bib0026 article-title: Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm publication-title: Inf. Sci. – volume: 41 start-page: 362 year: 2016 end-page: 372 ident: bib0037 article-title: Artificial bee colony algorithm with memory publication-title: Appl. Soft. Comput. – volume: 2712-2717 start-page: 2524 year: 2016 end-page: 2531 ident: bib0053 article-title: Search experience-based search adaptation in artificial bee colony algorithm publication-title: Proceedings of the IEEE Congress on Evolutionary Computation (CEC) – volume: 34 start-page: 851 year: 2015 end-page: 861 ident: bib0032 article-title: Artificial bee colony algorithm with distribution-based update rule publication-title: Appl. Soft. Comput. – start-page: 1114 year: 2015 end-page: 1120 ident: bib0007 publication-title: Efficient benchmarking of hyperparameter optimizers via surrogates – volume: 214 start-page: 108 year: 2009 end-page: 132 ident: bib0014 article-title: A comparative study of artificial bee colony algorithm publication-title: Appl. Math. Comput. – volume: 49 start-page: 4811 year: 2013 end-page: 4816 ident: bib0021 article-title: An improved artificial bee colony algorithm for optimal design of electromagnetic devices publication-title: IEEE Trans. Magn. – volume: 43 start-page: 1340 year: 2012 end-page: 1345 ident: bib0028 article-title: An adaptive artificial bee colony algorithm for long-term economic dispatch in cascaded hydropower systems publication-title: Electr. Power Energy Syst. – volume: 12 start-page: 3063 year: 2012 end-page: 3078 ident: bib0043 article-title: Parameter control system of evolutionary algorithm that is aided by the entire search history publication-title: Appl. Soft. Comput. – year: 2005 ident: bib0012 article-title: An Idea Based on Honey Bee Swarm for Numerical Optimization – volume: 11 start-page: 652 year: 2011 end-page: 657 ident: bib0019 article-title: A novel clustering approach: artificial bee colony (ABC) algorithm publication-title: Appl. Soft. Comput. – start-page: 318 year: 2007 end-page: 329 ident: bib0050 article-title: Modeling Decisions for Artificial intelligence, Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks, LNCS 4617/2007 – start-page: 822 year: 2017 end-page: 829 ident: bib0009 article-title: Efficient hyperparameter optimization for deep learning algorithms using deterministic RBF surrogates publication-title: AAAI. – volume: 111 start-page: 871 year: 2011 end-page: 882 ident: bib0040 article-title: Improved artificial bee colony algorithm for global optimization publication-title: Inf. Process. Lett. – volume: 43 start-page: 1011 year: 2013 end-page: 1024 ident: bib0033 article-title: A novel artificial bee colony algorithm based on modified search equation and orthogonal learning publication-title: IEEE Trans. Cybern. – volume: 217 start-page: 3166 year: 2010 end-page: 3173 ident: bib0029 article-title: Gbest-guided artificial bee colony algorithm for numerical function optimization publication-title: Appl. Math. Comput. – volume: 49 start-page: 423 year: 2016 end-page: 436 ident: bib0054 article-title: An adaptive and hybrid artificial bee colony algorithm (aABC) for ANFIS training publication-title: Appl. Soft. Comput. – volume: 109 start-page: 1 year: 2016 end-page: 16 ident: bib0056 article-title: Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion publication-title: Knowl. Based Syst. – year: 1997 ident: bib0045 article-title: Elements of Artificial Neural Networks – volume: 26 start-page: 454 year: 2015 end-page: 462 ident: bib0035 article-title: A directed artificial bee colony algorithm publication-title: Appl. Soft. Comput. – volume: 42 start-page: 21 year: 2014 end-page: 57 ident: bib0013 article-title: A comprehensive survey: artificial bee colony (abc) algorithm and applications publication-title: Artif. Intell. Rev. – volume: 18 start-page: 1527 year: 2006 end-page: 1554 ident: bib0001 article-title: A fast learning algorithm for deep belief nets publication-title: Neural Comput. – volume: 192 start-page: 120 year: 2012 end-page: 142 ident: bib0031 article-title: A modified artificial bee colony algorithm for real-parameter optimization publication-title: Inf. Sci. – volume: 10 start-page: 307 year: 2013 end-page: 322 ident: bib0027 article-title: An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process publication-title: IEEE Trans. Autom. Sci. Eng. – volume: 106 start-page: 570 year: 1998 end-page: 584 ident: bib0048 article-title: Global optimization for artificial neural networks: a tabu search application publication-title: Eur J Oper Res – start-page: 235 year: 2014 end-page: 241 ident: bib0039 article-title: A novel chaotic artificial bee colony algorithm based on tent map publication-title: Proceedings of the IEEE Congress on Evolutionary Computation (CEC) – volume: 301 start-page: 44 year: 2015 end-page: 60 ident: bib0016 article-title: An image watermarking scheme in wavelet domain with optimized compensation of singular value decomposition via artificial bee colony publication-title: Inf. Sci. – volume: 46 start-page: 1311 year: 2016 end-page: 1324 ident: bib0038 article-title: An improved artificial bee colony algorithm for solving hybrid flexible flowshop with dynamic operation skipping publication-title: IEEE Trans. Cybern. – start-page: 16 year: 2013 end-page: 21 ident: bib0011 publication-title: Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures – start-page: 1026 year: 2015 end-page: 1034 ident: bib0003 article-title: Delving deep into rectifiers: surpassing human-level performance on imagenet classification publication-title: Proceedings of the IEEE International Conference on Computer Vision. – volume: 13 start-page: 281 year: 2012 end-page: 305 ident: bib0005 article-title: Random search for hyper-parameter optimization publication-title: J. Mach. Learn. Res. – volume: 45 start-page: 373 year: 2015 end-page: 384 ident: bib0025 article-title: Combining artificial bee colony with ordinal optimization for stochastic economic lot scheduling problem publication-title: IEEE Trans. Syst. Man Cybern. Syst. – volume: 26 start-page: 1403 year: 2015 end-page: 1416 ident: bib0023 article-title: Incremental support vector learning for ordinal regression publication-title: IEEE Trans. Neural Net. Learn. Syst. – volume: 5 start-page: 4308 year: 2014 ident: bib0002 article-title: Searching for exotic particles in high-energy physics with deep learning publication-title: Nat. Commun. – volume: 295 start-page: 145 year: 2015 end-page: 159 ident: bib0024 article-title: Self-generated fuzzy systems design using artificial bee colony optimization publication-title: Inf. Sci. – year: 2005 ident: bib0047 article-title: Training feed-forward neural networks with ant colony optimization: an application to pattern classification publication-title: Proceedings of the Fifth International Conference on Hybrid intelligent systems, HIS – volume: 87 start-page: 1423 year: 1999 end-page: 1447 ident: bib0046 article-title: Evolving artificial neural networks publication-title: Proc. IEEE – volume: 15 start-page: 3460 year: 2015 end-page: 3468 ident: bib0008 article-title: Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves publication-title: IJCAI. – volume: 50 start-page: 737 year: 2014 end-page: 740 ident: bib0020 article-title: A modification of artificial bee colony algorithm applied to loudspeaker design problem publication-title: IEEE Trans. Magn. – start-page: 2712 year: 2016 end-page: 2717 ident: bib0052 article-title: An superior tracking artificial bee colony for global optimization problems publication-title: Proceedings of the IEEE Congress on Evolutionary Computation (CEC) – volume: 29 start-page: 82 year: 2012 end-page: 97 ident: bib0004 article-title: Deep neural networks for acoustic modelling in speech recognition: the shared views of four research groups publication-title: IEEE Signal Process. Mag. – volume: 55 start-page: 384 year: 2017 end-page: 401 ident: bib0051 article-title: An adaptive artificial bee colony algorithm based on objective function value information publication-title: Appl. Soft. Comput. – volume: 18 start-page: 6765 year: 2017 end-page: 6816 ident: bib0006 article-title: Hyperband: a novel bandit-based approach to hyperparameter optimization publication-title: J. Mach. Learn. Res. – volume: 39 start-page: 687 year: 2012 end-page: 697 ident: bib0030 article-title: A modified artificial bee colony algorithm publication-title: Comput. Oper. Res. – volume: 281 start-page: 443 year: 2014 end-page: 461 ident: bib0022 article-title: Optimal filter design using an improved artificial bee colony algorithm publication-title: Inf. Sci. – volume: 23 start-page: 227 year: 2014 end-page: 238 ident: bib0034 article-title: A quick artificial bee colony (qABC) algorithm and its performance on optimization problems publication-title: Appl. Soft. Comput. – volume: 3 start-page: 82 year: 1999 end-page: 102 ident: bib0042 article-title: Evolutionary programming made faster publication-title: IEEE Trans. Evol. Comput. – volume: 28 start-page: 69 year: 2015 end-page: 80 ident: bib0018 article-title: Dynamic clustering with improved binary artificial bee colony algorithm publication-title: Appl. Soft. Comput. – volume: 42 start-page: 1573 year: 2015 end-page: 1601 ident: bib0017 article-title: Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur's, Otsu and Tsallis functions publication-title: Expert Syst. Appl. – volume: 67 start-page: 278 year: 2014 end-page: 289 ident: bib0055 article-title: Tuning extreme learning machine by an improved artificial bee colony to model and optimize the boiler efficiency publication-title: Knowl. Based Syst. – start-page: 4 year: 2015 ident: bib0010 article-title: Optimizing deep learning hyper-parameters through an evolutionary algorithm publication-title: Proceedings of the Workshop on Machine Learning in High-Performance Computing Environments – volume: 300 start-page: 140 year: 2015 end-page: 157 ident: bib0036 article-title: Artificial bee colony algorithm with variable search strategy for continuous optimization publication-title: Inf. Sci. – year: 1990 ident: bib0044 article-title: Neural-Network Architectures: An Introduction – volume: 107 start-page: 14 year: 2016 end-page: 31 ident: bib0015 article-title: An improved artificial bee colony and its application publication-title: Knowl. Based Syst. – volume: 114 start-page: 589 year: 1999 end-page: 601 ident: bib0049 article-title: Optimization of neural networks: a comparative analysis of the genetic algorithm and simulated annealing publication-title: Eur. J. Oper. Res. – volume: 217 start-page: 3166 issue: 7 year: 2010 ident: 10.1016/j.neucom.2019.04.086_bib0029 article-title: Gbest-guided artificial bee colony algorithm for numerical function optimization publication-title: Appl. Math. Comput. – volume: 109 start-page: 1 year: 2016 ident: 10.1016/j.neucom.2019.04.086_bib0056 article-title: Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2016.06.014 – volume: 214 start-page: 108 issue: 1 year: 2009 ident: 10.1016/j.neucom.2019.04.086_bib0014 article-title: A comparative study of artificial bee colony algorithm publication-title: Appl. Math. Comput. – year: 1990 ident: 10.1016/j.neucom.2019.04.086_bib0044 – volume: 43 start-page: 1011 issue: 3 year: 2013 ident: 10.1016/j.neucom.2019.04.086_bib0033 article-title: A novel artificial bee colony algorithm based on modified search equation and orthogonal learning publication-title: IEEE Trans. Cybern. doi: 10.1109/TSMCB.2012.2222373 – volume: 50 start-page: 737 issue: 2 year: 2014 ident: 10.1016/j.neucom.2019.04.086_bib0020 article-title: A modification of artificial bee colony algorithm applied to loudspeaker design problem publication-title: IEEE Trans. Magn. doi: 10.1109/TMAG.2013.2281818 – volume: 114 start-page: 589 issue: 3 year: 1999 ident: 10.1016/j.neucom.2019.04.086_bib0049 article-title: Optimization of neural networks: a comparative analysis of the genetic algorithm and simulated annealing publication-title: Eur. J. Oper. Res. doi: 10.1016/S0377-2217(98)00114-3 – volume: 23 start-page: 227 year: 2014 ident: 10.1016/j.neucom.2019.04.086_bib0034 article-title: A quick artificial bee colony (qABC) algorithm and its performance on optimization problems publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2014.06.035 – volume: 3 start-page: 82 issue: 2 year: 1999 ident: 10.1016/j.neucom.2019.04.086_bib0042 article-title: Evolutionary programming made faster publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.771163 – volume: 87 start-page: 1423 issue: 9 year: 1999 ident: 10.1016/j.neucom.2019.04.086_bib0046 article-title: Evolving artificial neural networks publication-title: Proc. IEEE doi: 10.1109/5.784219 – volume: 42 start-page: 21 issue: 1 year: 2014 ident: 10.1016/j.neucom.2019.04.086_bib0013 article-title: A comprehensive survey: artificial bee colony (abc) algorithm and applications publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-012-9328-0 – volume: 192 start-page: 120 year: 2012 ident: 10.1016/j.neucom.2019.04.086_bib0031 article-title: A modified artificial bee colony algorithm for real-parameter optimization publication-title: Inf. Sci. doi: 10.1016/j.ins.2010.07.015 – volume: 26 start-page: 454 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0035 article-title: A directed artificial bee colony algorithm publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2014.10.020 – start-page: 822 year: 2017 ident: 10.1016/j.neucom.2019.04.086_bib0009 article-title: Efficient hyperparameter optimization for deep learning algorithms using deterministic RBF surrogates publication-title: AAAI. – start-page: 2712 year: 2016 ident: 10.1016/j.neucom.2019.04.086_bib0052 article-title: An superior tracking artificial bee colony for global optimization problems – start-page: 235 year: 2014 ident: 10.1016/j.neucom.2019.04.086_bib0039 article-title: A novel chaotic artificial bee colony algorithm based on tent map – volume: 107 start-page: 14 year: 2016 ident: 10.1016/j.neucom.2019.04.086_bib0015 article-title: An improved artificial bee colony and its application publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2016.05.052 – volume: 2712-2717 start-page: 2524 year: 2016 ident: 10.1016/j.neucom.2019.04.086_bib0053 article-title: Search experience-based search adaptation in artificial bee colony algorithm – start-page: 1026 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0003 article-title: Delving deep into rectifiers: surpassing human-level performance on imagenet classification – volume: 18 start-page: 1527 issue: 7 year: 2006 ident: 10.1016/j.neucom.2019.04.086_bib0001 article-title: A fast learning algorithm for deep belief nets publication-title: Neural Comput. doi: 10.1162/neco.2006.18.7.1527 – volume: 300 start-page: 140 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0036 article-title: Artificial bee colony algorithm with variable search strategy for continuous optimization publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.12.043 – volume: 45 start-page: 373 issue: 3 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0025 article-title: Combining artificial bee colony with ordinal optimization for stochastic economic lot scheduling problem publication-title: IEEE Trans. Syst. Man Cybern. Syst. doi: 10.1109/TSMC.2014.2351783 – volume: 12 start-page: 3063 issue: 9 year: 2012 ident: 10.1016/j.neucom.2019.04.086_bib0043 article-title: Parameter control system of evolutionary algorithm that is aided by the entire search history publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2012.05.008 – volume: 34 start-page: 851 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0032 article-title: Artificial bee colony algorithm with distribution-based update rule publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2015.05.041 – volume: 42 start-page: 1573 issue: 3 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0017 article-title: Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur's, Otsu and Tsallis functions publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2014.09.049 – volume: 43 start-page: 1340 issue: 1 year: 2012 ident: 10.1016/j.neucom.2019.04.086_bib0028 article-title: An adaptive artificial bee colony algorithm for long-term economic dispatch in cascaded hydropower systems publication-title: Electr. Power Energy Syst. doi: 10.1016/j.ijepes.2012.04.009 – volume: 28 start-page: 69 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0018 article-title: Dynamic clustering with improved binary artificial bee colony algorithm publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2014.11.040 – start-page: 1114 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0007 – volume: 281 start-page: 443 year: 2014 ident: 10.1016/j.neucom.2019.04.086_bib0022 article-title: Optimal filter design using an improved artificial bee colony algorithm publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.05.033 – start-page: 318 year: 2007 ident: 10.1016/j.neucom.2019.04.086_bib0050 – volume: 26 start-page: 1403 issue: 7 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0023 article-title: Incremental support vector learning for ordinal regression publication-title: IEEE Trans. Neural Net. Learn. Syst. doi: 10.1109/TNNLS.2014.2342533 – volume: 5 start-page: 4308 year: 2014 ident: 10.1016/j.neucom.2019.04.086_bib0002 article-title: Searching for exotic particles in high-energy physics with deep learning publication-title: Nat. Commun. doi: 10.1038/ncomms5308 – year: 2005 ident: 10.1016/j.neucom.2019.04.086_bib0012 – volume: 46 start-page: 1311 issue: 6 year: 2016 ident: 10.1016/j.neucom.2019.04.086_bib0038 article-title: An improved artificial bee colony algorithm for solving hybrid flexible flowshop with dynamic operation skipping publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2015.2444383 – volume: 111 start-page: 871 issue: 17 year: 2011 ident: 10.1016/j.neucom.2019.04.086_bib0040 article-title: Improved artificial bee colony algorithm for global optimization publication-title: Inf. Process. Lett. doi: 10.1016/j.ipl.2011.06.002 – volume: 55 start-page: 384 year: 2017 ident: 10.1016/j.neucom.2019.04.086_bib0051 article-title: An adaptive artificial bee colony algorithm based on objective function value information publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2017.01.031 – volume: 49 start-page: 423 year: 2016 ident: 10.1016/j.neucom.2019.04.086_bib0054 article-title: An adaptive and hybrid artificial bee colony algorithm (aABC) for ANFIS training publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2016.07.039 – year: 1997 ident: 10.1016/j.neucom.2019.04.086_bib0045 – volume: 295 start-page: 145 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0024 article-title: Self-generated fuzzy systems design using artificial bee colony optimization publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.10.008 – volume: 41 start-page: 362 year: 2016 ident: 10.1016/j.neucom.2019.04.086_bib0037 article-title: Artificial bee colony algorithm with memory publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2015.12.046 – volume: 31 start-page: 635 issue: 4 year: 2005 ident: 10.1016/j.neucom.2019.04.086_bib0041 article-title: A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems publication-title: J. Glob. Optim. doi: 10.1007/s10898-004-9972-2 – volume: 67 start-page: 278 year: 2014 ident: 10.1016/j.neucom.2019.04.086_bib0055 article-title: Tuning extreme learning machine by an improved artificial bee colony to model and optimize the boiler efficiency publication-title: Knowl. Based Syst. doi: 10.1016/j.knosys.2014.04.042 – volume: 18 start-page: 6765 issue: 1 year: 2017 ident: 10.1016/j.neucom.2019.04.086_bib0006 article-title: Hyperband: a novel bandit-based approach to hyperparameter optimization publication-title: J. Mach. Learn. Res. – volume: 49 start-page: 4811 issue: 8 year: 2013 ident: 10.1016/j.neucom.2019.04.086_bib0021 article-title: An improved artificial bee colony algorithm for optimal design of electromagnetic devices publication-title: IEEE Trans. Magn. doi: 10.1109/TMAG.2013.2241447 – volume: 15 start-page: 3460 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0008 article-title: Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves publication-title: IJCAI. – start-page: 4 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0010 article-title: Optimizing deep learning hyper-parameters through an evolutionary algorithm – start-page: 16 year: 2013 ident: 10.1016/j.neucom.2019.04.086_bib0011 – volume: 39 start-page: 687 issue: 3 year: 2012 ident: 10.1016/j.neucom.2019.04.086_bib0030 article-title: A modified artificial bee colony algorithm publication-title: Comput. Oper. Res. doi: 10.1016/j.cor.2011.06.007 – volume: 29 start-page: 82 issue: 6 year: 2012 ident: 10.1016/j.neucom.2019.04.086_bib0004 article-title: Deep neural networks for acoustic modelling in speech recognition: the shared views of four research groups publication-title: IEEE Signal Process. Mag. doi: 10.1109/MSP.2012.2205597 – volume: 106 start-page: 570 issue: 2-3 year: 1998 ident: 10.1016/j.neucom.2019.04.086_bib0048 article-title: Global optimization for artificial neural networks: a tabu search application publication-title: Eur J Oper Res doi: 10.1016/S0377-2217(97)00292-0 – volume: 13 start-page: 281 issue: 1 year: 2012 ident: 10.1016/j.neucom.2019.04.086_bib0005 article-title: Random search for hyper-parameter optimization publication-title: J. Mach. Learn. Res. – volume: 316 start-page: 487 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0026 article-title: Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.10.009 – volume: 10 start-page: 307 issue: 2 year: 2013 ident: 10.1016/j.neucom.2019.04.086_bib0027 article-title: An effective artificial bee colony algorithm for a real-world hybrid flowshop problem in steelmaking process publication-title: IEEE Trans. Autom. Sci. Eng. doi: 10.1109/TASE.2012.2204874 – volume: 301 start-page: 44 year: 2015 ident: 10.1016/j.neucom.2019.04.086_bib0016 article-title: An image watermarking scheme in wavelet domain with optimized compensation of singular value decomposition via artificial bee colony publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.12.042 – volume: 11 start-page: 652 issue: 1 year: 2011 ident: 10.1016/j.neucom.2019.04.086_bib0019 article-title: A novel clustering approach: artificial bee colony (ABC) algorithm publication-title: Appl. Soft. Comput. doi: 10.1016/j.asoc.2009.12.025 – year: 2005 ident: 10.1016/j.neucom.2019.04.086_bib0047 article-title: Training feed-forward neural networks with ant colony optimization: an application to pattern classification |
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