Improved Black Hole optimization algorithm for data clustering

Hasan Deeb1, Archana Sarangi1, Debahuti Mishra1, Shubhendu Kumar Sarangi2
1Department of Computer Science Engineering, Siksha 'O' Anusandhan Deemed to be University, Bhubaneswar, Odisha, India
2Department of Electronics & Instrumentation Engineering, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India

Tóm tắt

Từ khóa


Tài liệu tham khảo

Abdulwahab, 2019, An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems, IEEE Access, 7, 142085, 10.1109/ACCESS.2019.2937021

Azizipanah-Abarghooee, 2014, Short-term scheduling of thermal power systems using hybrid gradient based modified teaching–learning optimizer with black hole algorithm, Electr. Power Syst. Res., 108, 16, 10.1016/j.epsr.2013.10.012

Bäck, 1991, A survey of evolutionary strategies, 9

Bernal, 2020, Fuzzy galactic swarm optimization with dynamic adjustment of parameters based on fuzzy logic, SN Comput. Sci., 1, 10.1007/s42979-020-0062-4

Bouyer, 2018, An efficient hybrid clustering method based on improved cuckoo optimization and modified particle swarm optimization algorithms, Appl. Soft Comput., 67, 172, 10.1016/j.asoc.2018.03.011

Brezočnik, 2018, Swarm intelligence algorithms for feature selection: a review, Appl. Sci., 8, 10.3390/app8091521

Darwish, 2018, Bio-inspired computing: Algorithms review, deep analysis, and the scope of applications, Future Comput. Inf. J., 3, 231, 10.1016/j.fcij.2018.06.001

Dhanachandra, 2020, A new hybrid image segmentation approach using clustering and black hole algorithm, Comput. Intell., 1–20

Erol, 2006, A new optimization method: big bang–big crunch, Adv. Eng. Softw., 37, 106, 10.1016/j.advengsoft.2005.04.005

Frank, A., Asuncion, A., 2010. {UCI} Machine Learning Repository.

Hatamlou, 2013, Black hole: A new heuristic optimization approach for data clustering, Inf. Sci., 222, 175, 10.1016/j.ins.2012.08.023

Haupt, R.L., Haupt, S.E., Wiley, A.J., 2004. Practical Genetic Algorithms.

Ishak Boushaki, 2018, A new quantum chaotic cuckoo search algorithm for data clustering, Expert Syst. Appl., 96, 358, 10.1016/j.eswa.2017.12.001

Jensi, 2016, An improved krill herd algorithm with global exploration capability for solving numerical function optimization problems and its application to data clustering, Appl. Soft Comput., 46, 230, 10.1016/j.asoc.2016.04.026

Kiranyaz, 2014, Particle swarm optimization, Adapt. Learn. Optim., 15, 45

Mirjalili, 2019, Ant colony optimisation. Stud, Comput. Intell., 780, 33

Mirjalili, 2014, Grey wolf optimizer, Adv. Eng. Softw., 69, 46, 10.1016/j.advengsoft.2013.12.007

Mohammed, S.K., Ibrahim, Z., 2016. White Hole-Black Hole Algorithm.

Montgomery, 2009, Michell, Laplace and the origin of the black hole concept, J. Astron. Hist. Herit., 12, 90, 10.3724/SP.J.1440-2807.2009.02.01

Nemati, 2014, Black Holes Algorithm with fuzzy hawking radiation, Int. J. Sci. Technol. Res., 3, 85

Nobile, 2018, Fuzzy self-tuning PSO: a settings-free algorithm for global optimization, Swarm Evol. Comput., 39, 70, 10.1016/j.swevo.2017.09.001

Pal, R., Saraswat, M., 2018. Data clustering using enhanced biogeography-based optimization. In: 2017 10th Int. Conf. Contemp. Comput. IC3 2017 2018-Janua, 1–6. https://doi.org/10.1109/IC3.2017.8284305.

Pashaei, 2017, Binary black hole algorithm for feature selection and classification on biological data, Appl. Soft Comput., 56, 94, 10.1016/j.asoc.2017.03.002

Pashaei, E., Ozen, M., Aydin, N., 2015. An application of black hole algorithm and decision tree for medical problem. In: 2015 IEEE 15th Int. Conf. Bioinforma. Bioeng. BIBE 2015. https://doi.org/10.1109/BIBE.2015.7367738.

Rashedi, 2009, GSA: a gravitational search algorithm, Inf. Sci., 179, 2232, 10.1016/j.ins.2009.03.004

Rodriguez, 2019, Clustering algorithms: a comparative approach, PLoS ONE

Soto, 2018, Adaptive black hole algorithm for solving the set covering problem, Math. Probl. Eng., 2018, 10.1155/2018/2183214

Srinivas, M., Patnaik, L.M., 1994. Genetic Algorithms: A Survey. Computer (Long. Beach. Calif). 27, 17–26. https://doi.org/10.1109/2.294849.

Tayarani, M.H., Akbarzadeh. T., N.M.R., 2008. Magnetic optimization algorithms a new synthesis. 2008 IEEE Congr. Evol. Comput. CEC 2008 2659–2664. https://doi.org/10.1109/CEC.2008.4631155.

Vora, 2013, A survey on K-mean clustering and particle swarm optimization 25 Fig. 1 flowchart of K-mean, Int. J. Sci. Mod. Eng., 1, 2319

Xie, 2020, Extreme learning machine soft-sensor model with different activation functions on grinding process optimized by improved black hole algorithm, IEEE Access, 8, 25084, 10.1109/ACCESS.2020.2970429

Yaghoobi, S., Hemayat, S., Mojallali, H., 2015. Image gray-level enhancement using Black Hole algorithm. In: 2015 2nd Int. Conf. Pattern Recognit. Image Anal. IPRIA 2015 9–13. https://doi.org/10.1109/PRIA.2015.7161633.

Yaghoobi, 2016, Modified Black Hole algorithm with genetic operators, Int. J. Comput. Intell. Syst., 9, 652, 10.1080/18756891.2016.1204114

Yang, 2010, Bat-inspired Algorithm, Stud Comput. Intell., 284, 65, 10.1007/978-3-642-12538-6_6

Yepes, 2020, Black hole algorithm for sustainable design of counterfort retaining walls, Sustainability, 12, 1, 10.3390/su12072767

Zhou, 2019, Automatic data clustering using nature-inspired symbiotic organism search algorithm, Knowl.-Based Syst., 163, 546, 10.1016/j.knosys.2018.09.013