So sánh toàn diện các hàm fitness dựa trên độ chính xác của thuật toán metaheuristic cho việc lựa chọn đặc trưng

Abdel-Basset M, Ding W, El-Shahat D (2020a) A hybrid Harris Hawks optimization algorithm with simulated annealing for feature selection. Artif Intell Rev 154:1–45 Abdel-Basset M, El-Shahat D, El-henawy I, de Albuquerque VHC, Mirjalili S (2020b) A new fusion of grey wolf optimizer algorithm with a two-phase mutation for feature selection. Expert Syst Appl 139:112824 Agrawal R, Kaur B, Sharma S (2020) Quantum based whale optimization algorithm for wrapper feature selection. Appl Soft Comput 89:106092 Agrawal P, Abutarboush HF, Ganesh T, Mohamed AW (2021a) Metaheuristic algorithms on feature selection: a survey of one decade of research (2009–2019). IEEE Access 9:26766–26791 Agrawal P, Ganesh T, Mohamed AW (2021b) Chaotic gaining sharing knowledge-based optimization algorithm: an improved metaheuristic algorithm for feature selection. Soft Comput 25(14):9505–9528 Agrawal P, Ganesh T, Mohamed AW (2021c) A novel binary gaining–sharing knowledge-based optimization algorithm for feature selection. Neural Comput Appl 33(11):5989–6008 Agrawal P, Ganesh T, Oliva D, Mohamed AW (2022) S-shaped and V-shaped gaining-sharing knowledge-based algorithm for feature selection. Appl Intell 52(1):81–112 Al-Betar MA, Hammouri AI, Awadallah MA, Doush IA (2020) Binary β-hill climbing optimizer with S-shape transfer function for feature selection. J Ambient Intell Humaniz Comput 12:1–29 Al-Tashi Q, Kadir SJA, Rais HM, Mirjalili S, Alhussian H (2019) Binary optimization using hybrid grey wolf optimization for feature selection. IEEE Access 7:39496–39508 Alweshah M, Al Khalaileh S, Gupta BB, Almomani A, Hammouri AI, Al-Betar MA (2020) The monarch butterfly optimization algorithm for solving feature selection problems. Neural Comput Appl 34:1–15 Arora S, Anand P (2019) Binary butterfly optimization approaches for feature selection. Expert Syst Appl 116:147–160 Arora S, Sharma M, Anand P (2020) A novel chaotic interior search algorithm for global optimization and feature selection. Appl Artif Intell 34(4):292–328 Asuncion A, Newman D (2007) UCI machine learning repository. Irvine, CA, USA Awadallah MA, Al-Betar MA, Hammouri AI, Alomari OA (2020) Binary JAYA algorithm with adaptive mutation for feature selection. Arab J Sci Eng 45(12):10875–10890 Babalik A, Cinar AC, Kiran MS (2018a) A modification of tree-seed algorithm using Deb’s rules for constrained optimization. Appl Soft Comput 63:289–305 Babalik A, Ozkis A, Uymaz SA, Kiran MS (2018b) A multi-objective artificial algae algorithm. Appl Soft Comput 68:377–395 Brezočnik L, Fister I, Podgorelec V (2018) Swarm intelligence algorithms for feature selection: a review. Appl Sci 8(9):1521 Chegini SN, Bagheri A, Najafi F (2018) PSOSCALF: A new hybrid PSO based on Sine Cosine Algorithm and Levy flight for solving optimization problems. Appl Soft Comput 73:697–726 Chuang L-Y, Chang H-W, Tu C-J, Yang C-H (2008) Improved binary PSO for feature selection using gene expression data. Comput Biol Chem 32(1):29–38 Cinar AC, Kiran MS (2018) Similarity and logic gate-based tree-seed algorithms for binary optimization. Comput Ind Eng 115:631–646 Derrac J, García S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3–18 Ding Y, Zhou K, Bi W (2020) Feature selection based on hybridization of genetic algorithm and competitive swarm optimizer. Soft Comput 24:1–10 El-Kenawy E-SM, Eid MM, Saber M, Ibrahim A (2020) MbGWO-SFS: modified binary grey wolf optimizer based on stochastic fractal search for feature selection. IEEE Access 8:107635–107649 Emary E, Zawbaa HM (2019) Feature selection via Lèvy Antlion optimization. Pattern Anal Appl 22(3):857–876 Emary E, Zawbaa HM, Hassanien AE (2016a) Binary ant lion approaches for feature selection. Neurocomputing 213:54–65 Emary E, Zawbaa HM, Hassanien AE (2016b) Binary grey wolf optimization approaches for feature selection. Neurocomputing 172:371–381 Emary E, Zawbaa HM, Sharawi M (2019) Impact of Lèvy flight on modern meta-heuristic optimizers. Appl Soft Comput 75:775–789 Emine B, Ülker E (2020) An efficient binary social spider algorithm for feature selection problem. Expert Syst Appl 146:113185 Enache A-C, Sgarciu V, Petrescu-Niţă A (2015) Intelligent feature selection method rooted in Binary Bat Algorithm for intrusion detection. In: Paper presented at the 2015 IEEE 10th jubilee international symposium on applied computational intelligence and informatics Faris H, Mafarja MM, Heidari AA, Aljarah I, Ala’M A-Z, Mirjalili S, Fujita H (2018) An efficient binary salp swarm algorithm with crossover scheme for feature selection problems. Knowl Based Syst 154:43–67 Gao Y, Zhou Y, Luo Q (2020) An efficient binary equilibrium optimizer algorithm for feature selection. IEEE Access 8:140936–140963 Gholami J, Pourpanah F, Wang X (2020) Feature selection based on improved binary global harmony search for data classification. Appl Soft Comput 93:106402 Ghosh KK, Singh PK, Hong J, Geem ZW, Sarkar R (2020) Binary social mimic optimization algorithm with X-shaped transfer function for feature selection. IEEE Access 8:97890–97906 Guha R, Ghosh M, Chakrabarti A, Sarkar R, Mirjalili S (2020a) Introducing clustering based population in binary gravitational search algorithm for feature selection. Appl Soft Comput 93:106341 Guha R, Ghosh M, Mutsuddi S, Sarkar R, Mirjalili S (2020b) Embedded chaotic whale survival algorithm for filter-wrapper feature selection. Soft Comput 24:12821–12843 Haklı H, Uğuz H (2014) A novel particle swarm optimization algorithm with Levy flight. Appl Soft Comput 23:333–345 Hammouri AI, Mafarja M, Al-Betar MA, Awadallah MA, Abu-Doush I (2020) An improved dragonfly algorithm for feature selection. Knowl Based Syst 203:106131 Han C, Zhou G, Zhou Y (2019) Binary symbiotic organism search algorithm for feature selection and analysis. IEEE Access 7:166833–166859 He X, Zhang Q, Sun N, Dong Y (2009) Feature selection with discrete binary differential evolution. Paper presented at the 2009 international conference on artificial intelligence and computational intelligence Hegazy AE, Makhlouf M, El-Tawel GS (2020) Improved salp swarm algorithm for feature selection. J King Saud Univ Comput Inf Sci 32(3):335–344 Heidari AA, Pahlavani P (2017) An efficient modified grey wolf optimizer with Lévy flight for optimization tasks. Appl Soft Comput 60:115–134 Houssein EH, Saad MR, Hashim FA, Shaban H, Hassaballah M (2020) Lévy flight distribution: a new metaheuristic algorithm for solving engineering optimization problems. Eng Appl Artif Intell 94:103731 Hu B, Dai Y, Su Y, Moore P, Zhang X, Mao C, Chen J, Xu L (2016) Feature selection for optimized high-dimensional biomedical data using an improved shuffled frog leaping algorithm. IEEE/ACM Trans Comput Biol Bioinform 15(6):1765–1773 Hussien, A. G., Houssein, E. H., & Hassanien, A. E. (2017). A binary whale optimization algorithm with hyperbolic tangent fitness function for feature selection. Paper presented at the 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS). Jensi R, Jiji GW (2016) An enhanced particle swarm optimization with levy flight for global optimization. Appl Soft Comput 43:248–261 Jia H, Li J, Song W, Peng X, Lang C, Li Y (2019) Spotted hyena optimization algorithm with simulated annealing for feature selection. IEEE Access 7:71943–71962 Jiang Y, Luo Q, Wei Y, Abualigah L, Zhou Y (2021) An efficient binary gradient-based optimizer for feature selection. Math Biosci Eng 18(4):3813–3854 Karakoyun M, Ozkis A, Kodaz H (2020) A new algorithm based on gray wolf optimizer and shuffled frog leaping algorithm to solve the multi-objective optimization problems. Appl Soft Comput 96:106560 Karasekreter N, Şahman MA, Başçiftçi F, Fidan U (2020) PSO-based clustering for the optimization of energy consumption in wireless sensor network. Emerg Mater Res 9(3):776–783 Kaya E (2021) A comprehensive study of parameters analysis for galactic swarm optimization. Int J Intell Syst Appl Eng 9(1):28–37 Khurma RA, Aljarah I, Sharieh A (2021) A Simultaneous moth flame optimizer feature selection approach based on levy flight and selection operators for medical diagnosis. Arab J Sci Eng 46:1–26 Kiran MS (2015) TSA: tree-seed algorithm for continuous optimization. Expert Syst Appl 42(19):6686–6698 Korkmaz S, Kiran MS (2018) An artificial algae algorithm with stigmergic behavior for binary optimization. Appl Soft Comput 64:627–640 Korkmaz S, Babalik A, Kiran MS (2018) An artificial algae algorithm for solving binary optimization problems. Int J Mach Learn Cybern 9(7):1233–1247 Liu M, Yao X, Li Y (2020) Hybrid whale optimization algorithm enhanced with Lévy flight and differential evolution for job shop scheduling problems. Appl Soft Comput 87:105954 Mafarja M, Mirjalili S (2018) Whale optimization approaches for wrapper feature selection. Appl Soft Comput 62:441–453 Mafarja MM, Eleyan D, Jaber I, Hammouri A, Mirjalili S (2017) Binary dragonfly algorithm for feature selection. In: Paper presented at the 2017 international conference on new trends in computing sciences (ICTCS) Mafarja M, Aljarah I, Heidari AA, Hammouri AI, Faris H, Ala’M A-Z, Mirjalili S (2018) Evolutionary population dynamics and grasshopper optimization approaches for feature selection problems. Knowl Based Syst 145:25–45 Mafarja M, Aljarah I, Faris H, Hammouri AI, Ala’M A-Z, Mirjalili S (2019) Binary grasshopper optimisation algorithm approaches for feature selection problems. Expert Syst Appl 117:267–286 Magdziarz M, Szczotka W (2016) Quenched trap model for Lévy flights. Commun Nonlinear Sci Numer Simul 30(1–3):5–14 Mohamed A-AA, Hassan S, Hemeida A, Alkhalaf S, Mahmoud M, Eldin AMB (2020) Parasitism-predation algorithm (PPA): a novel approach for feature selection. Ain Shams Eng J 11(2):293–308 Nadimi-Shahraki MH, Zamani H (2022) DMDE: diversity-maintained multi-trial vector differential evolution algorithm for non-decomposition large-scale global optimization. Expert Syst Appl 198:116895 Nadimi-Shahraki MH, Fatahi A, Zamani H, Mirjalili S (2022a) Binary approaches of quantum-based avian navigation optimizer to select effective features from high-dimensional medical data. Mathematics 10(15):2770 Nadimi-Shahraki MH, Zamani H, Mirjalili S (2022b) Enhanced whale optimization algorithm for medical feature selection: a COVID-19 case study. Comput Biol Med 148:105858 Nakamura RY, Pereira LA, Costa KA, Rodrigues D, Papa JP, Yang X-S (2012) BBA: a binary bat algorithm for feature selection. In: Paper presented at the 2012 25th SIBGRAPI conference on graphics, patterns and images Nguyen BH, Xue B, Zhang M (2020) A survey on swarm intelligence approaches to feature selection in data mining. Swarm Evol Comput 54:100663 Ouadfel S, Abd Elaziz M (2020) Enhanced crow search algorithm for feature selection. Expert Syst Appl 159:113572 Özkış A, Babalık A (2017) A novel metaheuristic for multi-objective optimization problems: the multi-objective vortex search algorithm. Inf Sci 402:124–148 Pourpanah F, Shi Y, Lim CP, Hao Q, Tan CJ (2019) Feature selection based on brain storm optimization for data classification. Appl Soft Comput 80:761–775 Purushothaman R, Rajagopalan S, Dhandapani G (2020) Hybridizing gray wolf optimization (GWO) with grasshopper optimization algorithm (GOA) for text feature selection and clustering. Appl Soft Comput 96:106651 Sag T, Cunkas M (2016) A new ABC-based multiobjective optimization algorithm with an improvement approach (IBMO: improved bee colony algorithm for multiobjective optimization). Turk J Electr Eng Comput Sci 24(4):2349–2373 Şahman MA (2021) A discrete spotted hyena optimizer for solving distributed job shop scheduling problems. Appl Soft Comput 106:107349 Şahman MA, Çunkaş M, İnal Ş, İnal F, Coşkun B, Taşkiran U (2009) Cost optimization of feed mixes by genetic algorithms. Adv Eng Softw 40(10):965–974 Sahman MA, Altun AA, Dündar AO (2017) The binary differential search algorithm approach for solving uncapacitated facility location problems. J Comput Theor Nanosci 14(1):670–684 Şahman MA, Altun AA, Dündar AO (2018) A new MILP model proposal in feed formulation and using a hybrid-linear binary PSO (H-LBP) approach for alternative solutions. Neural Comput Appl 29(2):537–552 Sheikh KH, Ahmed S, Mukhopadhyay K, Singh PK, Yoon JH, Geem ZW, Sarkar R (2020) EHHM: electrical harmony based hybrid meta-heuristic for feature selection. IEEE Access 8:158125–158141 Tahir M, Tubaishat A, Al-Obeidat F, Shah B, Halim Z, Waqas M (2020) A novel binary chaotic genetic algorithm for feature selection and its utility in affective computing and healthcare. Neural Comput Appl 34:1–22 Tang D, Yang J, Dong S, Liu Z (2016) A Lévy flight-based shuffled frog-leaping algorithm and its applications for continuous optimization problems. Appl Soft Comput 49:641–662 Too J, Abdullah AR (2020) Chaotic atom search optimization for feature selection. Arab J Sci Eng 45:1–17 Too J, Mirjalili S (2021) General learning equilibrium optimizer: a new feature selection method for biological data classification. Appl Artif Intell 35(3):247–263 Too J, Abdullah AR, Mohd Saad N, Tee W (2019) EMG feature selection and classification using a Pbest-guide binary particle swarm optimization. Computation 7(1):12 Tu Q, Chen X, Liu X (2019) Multi-strategy ensemble grey wolf optimizer and its application to feature selection. Appl Soft Comput 76:16–30 Tubishat M, Ja’afar S, Alswaitti M, Mirjalili S, Idris N, Ismail MA, Omar MS (2020) Dynamic salp swarm algorithm for feature selection. Expert Syst Appl 164:113873 Turkoglu B, Uymaz SA, Kaya E (2022) Binary artificial algae algorithm for feature selection. Appl Soft Comput 120:108630 Uymaz SA, Tezel G, Yel E (2015) Artificial algae algorithm (AAA) for nonlinear global optimization. Appl Soft Comput 31:153–171 Wang Y, Li T (2020) Local feature selection based on artificial immune system for classification. Appl Soft Comput 87:105989 Wang R, Zhou Y, Qiao S, Huang K (2016) Flower pollination algorithm with bee pollinator for cluster analysis. Inf Process Lett 116(1):1–14 Wang X-H, Zhang Y, Sun X-Y, Wang Y-L, Du C-H (2020) Multi-objective feature selection based on artificial bee colony: an acceleration approach with variable sample size. Appl Soft Comput 88:106041 Wei W, Chen S, Lin Q, Ji J, Chen J (2020) A multi-objective immune algorithm for intrusion feature selection. Appl Soft Comput 95:106522 Xue B, Zhang M, Browne WN (2012a) New fitness functions in binary particle swarm optimisation for feature selection. In: Paper presented at the 2012a IEEE congress on evolutionary computation Xue B, Zhang M, Browne WN (2012b) Particle swarm optimization for feature selection in classification: a multi-objective approach. IEEE Trans Cybern 43(6):1656–1671 Xue B, Zhang M, Browne WN, Yao X (2015) A survey on evolutionary computation approaches to feature selection. IEEE Trans Evol Comput 20(4):606–626 Xue Y, Tang T, Pang W, Liu AX (2020) Self-adaptive parameter and strategy based particle swarm optimization for large-scale feature selection problems with multiple classifiers. Appl Soft Comput 88:106031 Yang X-S, Cui Z, Xiao R, Gandomi AH, Karamanoglu M (2013) Swarm intelligence and bio-inspired computation: theory and applications. Newnes, Lithgow Zamani H, Nadimi-Shahraki MH, Gandomi AH (2021) QANA: quantum-based avian navigation optimizer algorithm. Eng Appl Artif Intell 104:104314 Zamani H, Nadimi-Shahraki MH, Gandomi AH (2022) Starling murmuration optimizer: a novel bio-inspired algorithm for global and engineering optimization. Comput Methods Appl Mech Eng 392:114616 Zawbaa HM, Emary E, Grosan C, Snasel V (2018) Large-dimensionality small-instance set feature selection: a hybrid bio-inspired heuristic approach. Swarm Evol Comput 42:29–42 Zhang H, Xie J, Hu Q, Shao L, Chen T (2018) A hybrid DPSO with Levy flight for scheduling MIMO radar tasks. Appl Soft Comput 71:242–254 Zhou B, Liao X (2020) Particle filter and Levy flight-based decomposed multi-objective evolution hybridized particle swarm for flexible job shop greening scheduling with crane transportation. Appl Soft Comput 91:106217