Use Two Kind Hybridization of the Chaotic Peafowl Algorithm with the Hummingbird Algorithm
DOI:
https://doi.org/10.29304/jqcm.2022.14.4.1124Keywords:
Artificial Hummingbird Algorithm (AHA), Peafowl optimization algorithm (POA), Chaotic Map, Tent Chaotic Map, Gauss MapAbstract
The wide spread of living organisms in nature and how they obtain food has prompted many scientists to form mathematical models that simulate these organisms. These models were used to solve math problems that take a long time and effort to solve, but these models were sometimes weak and required modification. In this research we used two methods to reach the optimal solution, the first method we used the Peafowl optimization algorithm (POA) with the chaos function and the chaotic tent function to reach the optimal solution and this was the first step in the work, the second method we hybridized the first step by adding the artificial hummingbird algorithm (AHA) The hybridization was of two types, the first by linking communities and the second by linking equations, and we got the optimal solution using 1000 iterations in the two steps, which resulted in producing the optimal solution.
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References
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[2] Y. A. Fattah Hamoodi and S. A. M Ramadhan, “Identification of Biometrics based on a Classical Mathematical Methods in Forensic Medicine.,” Indian J. Forensic Med. Toxicol., vol. 13, no. 3, 2019.
[3] S. Desale, A. Rasool, S. Andhale, and P. Rane, “Heuristic and meta-heuristic algorithms and their relevance to the real world: a survey,” Int. J. Comput. Eng. Res. Trends, vol. 351, no. 5, pp. 2349–7084, 2015.
[4] B. Yang et al., “Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification,” Energy Convers. Manag., vol. 208, p. 112595, 2020.
[5] A. Kaveh and M. Khayatazad, “A new meta-heuristic method: ray optimization,” Comput. Struct., vol. 112, pp. 283–294, 2012.
[6] M. A. El Aziz, A. A. Ewees, and A. E. Hassanien, “Hybrid swarms optimization based image segmentation,” in Hybrid soft computing for image segmentation, Springer, 2016, pp. 1–21.
[7] P. Kenekayoro, “A Meta-Heuristic Search Algorithm based on Infrasonic Mating Displays in Peafowls,” arXiv Prepr. arXiv2106.14487, 2021.
[8] E. Asyabi, A. Bestavros, E. Sharafzadeh, and T. Zhu, “Peafowl: In-application cpu scheduling to reduce power consumption of in-memory key-value stores,” in Proceedings of the 11th ACM Symposium on Cloud Computing, 2020, pp. 150–164.
[9] J. Wang et al., “Novel phasianidae inspired peafowl (Pavo muticus/cristatus) optimization algorithm: Design, evaluation, and SOFC models parameter estimation,” Sustain. Energy Technol. Assessments, vol. 50, p. 101825, 2022.
[10] K. Sun, K. A. Meiklejohn, B. C. Faircloth, T. C. Glenn, E. L. Braun, and R. T. Kimball, “The evolution of peafowl and other taxa with ocelli (eyespots): a phylogenomic approach,” Proc. R. Soc. B Biol. Sci., vol. 281, no. 1790, p. 20140823, 2014.
[11] M. A. S. Ali, F. R. PP, and D. Salama Abd Elminaam, “A Feature Selection Based on Improved Artificial Hummingbird Algorithm Using Random Opposition-Based Learning for Solving Waste Classification Problem,” Mathematics, vol. 10, no. 15, p. 2675, 2022.
[12] B. S. Yildiz, P. Mehta, S. M. Sait, N. Panagant, S. Kumar, and A. R. Yildiz, “A new hybrid artificial hummingbird-simulated annealing algorithm to solve constrained mechanical engineering problems,” Mater. Test., vol. 64, no. 7, pp. 1043–1050, 2022.
[13] Yahia, W. B., Al-Neama, M. W., & Arif, G. E. (2020). PNACO: parallel algorithm for neighbour joining hybridized with ant colony optimization on multi-core system. Вестник Южно-Уральского государственного университета. Серия: Математическое моделирование и программирование, 13(4), 107-118.
[14] A. Fathy, “A novel artificial hummingbird algorithm for integrating renewable based biomass distributed generators in radial distribution systems,” Appl. Energy, vol. 323, p. 119605, 2022.
[15] E. N. Lorenz, “Deterministic nonperiodic flow,” J. Atmos. Sci., vol. 20, no. 2, pp. 130–141, 1963.
[16] Z. Hua, Y. Zhou, and H. Huang, “Cosine-transform-based chaotic system for image encryption,” Inf. Sci. (Ny)., vol. 480, pp. 403–419, 2019.
[17] S. F. Al-Azzawi and Z. S. Al-Talib, “Generalized function projective synchronization via nonlinear controller strategy,” J. Interdiscip. Math., pp. 1–13, 2022.
[18] Q. Lai, “A unified chaotic system with various coexisting attractors,” Int. J. Bifurc. Chaos, vol. 31, no. 01, p. 2150013, 2021.
[19] M. Alawida, A. Samsudin, J. Sen Teh, and R. S. Alkhawaldeh, “A new hybrid digital chaotic system with applications in image encryption,” Signal Processing, vol. 160, pp. 45–58, 2019.
[20] A. M. Sadoun, I. R. Najjar, G. S. Alsoruji, M. S. Abd-Elwahed, M. A. Elaziz, and A. Fathy, “Utilization of improved machine learning method based on artificial hummingbird algorithm to predict the tribological behavior of Cu-Al2O3 nanocomposites synthesized by in situ method,” Mathematics, vol. 10, no. 8, p. 1266, 2022.
[21] M. A. Hamida, R. A. El-Sehiemy, A. R. Ginidi, E. Elattar, and A. M. Shaheen, “Parameter identification and state of charge estimation of Li-Ion batteries used in electric vehicles using artificial hummingbird optimizer,” J. Energy Storage, vol. 51, p. 104535, 2022.
[22] S. Haddad, B. Lekouaghet, M. Benghanem, A. Soukkou, and A. Rabhi, “Parameter Estimation of Solar Modules Operating Under Outdoor Operational Conditions Using Artificial Hummingbird Algorithm,” IEEE Access, 2022.
[23] Yahia, W. B., Al-Neama, M. W., & Arif, G. E. (2020). A Hybrid Optimization Algorithm of Ant Colony Search and NeighbourJoining Method to Solve the Travelling Salesman Problem. Advanced Mathematical Models and Applications, 5(1), 95-110.
[24] O. W. Khalid, N. A. M. Isa, and H. A. M. Sakim, “Emperor penguin optimizer: A comprehensive review based on state-of-the-art meta-heuristic algorithms,” Alexandria Eng. J., 2022.
[25] R. Chaudhary and H. Banati, “Peafowl Algorithm,” in 2019 IEEE Congress on Evolutionary Computation (CEC), 2019, pp. 2331–2338.
[26] T. SAWANGTHAM and A. WIWEGWEAW, “Genetic diversity of green peafowl (Pavo muticus) in northern Thailand based on mitochondrial DNA control region sequences,” Trop. Nat. Hist., vol. 18, no. 1, pp. 11–23, 2018.
[27] L. G. C. Vithakshana and W. Samankula, “IoT based animal classification system using convolutional neural network,” in 2020 International Research Conference on Smart Computing and Systems Engineering (SCSE), 2020, pp. 90–95.
[28] A. Kanso and H. S. Own, “Steganographic algorithm based on a chaotic map,” Commun. Nonlinear Sci. Numer. Simul., vol. 17, no. 8, pp. 3287–3302, 2012.
[29] C. Pak and L. Huang, “A new color image encryption using combination of the 1D chaotic map,” Signal Processing, vol. 138, pp. 129–137, 2017.
[30] C. Han, “An image encryption algorithm based on modified logistic chaotic map,” Optik (Stuttg)., vol. 181, pp. 779–785, 2019.
[31] C. Li, G. Luo, K. Qin, and C. Li, “An image encryption scheme based on chaotic tent map,” Nonlinear Dyn., vol. 87, no. 1, pp. 127–133, 2017.
[32] S. Kanwal et al., “An Effective Color Image Encryption Based on Henon Map, Tent Chaotic Map, and Orthogonal Matrices,” Sensors, vol. 22, no. 12, p. 4359, 2022.
[33] F. Kuang, Z. Jin, W. Xu, and S. Zhang, “A novel chaotic artificial bee colony algorithm based on tent map,” in 2014 IEEE congress on evolutionary computation (CEC), 2014, pp. 235–241.
[34] J. A. de Oliveira, H. M. J. de Mendonça, V. A. Favarim, R. Carvalho, and E. D. Leonel, “Boundary crises and supertrack orbits in the Gauss map,” Eur. Phys. J. Spec. Top., pp. 1–4, 2022.
[35] E. Güler, H. H. Hacısalihoğlu, and Y. H. Kim, “The Gauss map and the third Laplace-Beltrami operator of the rotational hypersurface in 4-space,” Symmetry (Basel)., vol. 10, no. 9, p. 398, 2018.
[36] Younis, Y. S., Ali, A. H., Alhafidhb, O. K., Yahia, W. B., Alazzam, M. B., Hamad, A. A., & Meraf, Z. (2022). Early diagnosis of breast cancer using image processing techniques. Journal of Nanomaterials, 2022.
[37] X.-S. Yang, “Test problems in optimization,” arXiv Prepr. arXiv1008.0549, 2010.
[38] S. Arora and S. Singh, “Butterfly algorithm with levy flights for global optimization,” in 2015 International conference on signal processing, computing and control (ISPCC), 2015, pp. 220–224.
[39] X.-S. Yang and S. Deb, “Engineering optimisation by cuckoo search,” arXiv Prepr. arXiv1005.2908, 2010.
[40] X.-S. Yang, “Firefly algorithm, stochastic test functions and design optimisation,” arXiv Prepr. arXiv1003.1409, 2010.
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Published
2022-12-31
How to Cite
Alhamdany, Y. A., & Mitras, B. A. (2022). Use Two Kind Hybridization of the Chaotic Peafowl Algorithm with the Hummingbird Algorithm. Journal of Al-Qadisiyah for Computer Science and Mathematics, 14(4), Math Page 151–161. https://doi.org/10.29304/jqcm.2022.14.4.1124
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Math Articles
