{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T23:16:09Z","timestamp":1780355769896,"version":"3.54.1"},"reference-count":91,"publisher":"Springer Science and Business Media LLC","issue":"32","license":[{"start":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T00:00:00Z","timestamp":1723507200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T00:00:00Z","timestamp":1723507200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2023\/10419-0"],"award-info":[{"award-number":["2023\/10419-0"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["#2022\/10683-7"],"award-info":[{"award-number":["#2022\/10683-7"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["#2021\/06870-3"],"award-info":[{"award-number":["#2021\/06870-3"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004901","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais","doi-asserted-by":"publisher","award":["APQ-00385-18"],"award-info":[{"award-number":["APQ-00385-18"]}],"id":[{"id":"10.13039\/501100004901","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s00521-024-10155-9","type":"journal-article","created":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T13:03:13Z","timestamp":1723554193000},"page":"20493-20511","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Golden lichtenberg algorithm: a fibonacci sequence approach applied to feature selection"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9923-7419","authenticated-orcid":false,"given":"Jo\u00e3o Luiz Junho","family":"Pereira","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matheus Brendon","family":"Francisco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benedict Jun","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guilherme Ferreira","family":"Gomes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana Carolina","family":"Lorena","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,8,13]]},"reference":[{"key":"10155_CR1","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2019.113122","volume":"145","author":"M Tubishat","year":"2020","unstructured":"Tubishat M, Idris N, Shuib L, Abushariah MA, Mirjalili S (2020) Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection. Expert Syst Appl 145:113122","journal-title":"Expert Syst Appl"},{"key":"10155_CR2","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.eswa.2018.08.051","volume":"116","author":"S Arora","year":"2019","unstructured":"Arora S, Anand P (2019) Binary butterfly optimization approaches for feature selection. Expert Syst Appl 116:147\u2013160","journal-title":"Expert Syst Appl"},{"key":"10155_CR3","volume":"248","author":"BJ Ma","year":"2022","unstructured":"Ma BJ, Liu S, Heidari AA (2022) Multi-strategy ensemble binary hunger games search for feature selection. Knowl-Based Syst 248:108787","journal-title":"Knowl-Based Syst"},{"issue":"8","key":"10155_CR4","volume":"40","author":"JLJ Pereira","year":"2023","unstructured":"Pereira JLJ, Ma BJ, Francisco MB, Junior RFR, Gomes GF (2023) A comparison between chaos theory and L\u00e9vy flights in sunflower optimization for feature selection. Expert Syst 40(8):e13330","journal-title":"Expert Syst"},{"key":"10155_CR5","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113873","volume":"164","author":"M Tubishat","year":"2021","unstructured":"Tubishat M, Ja\u2019afarr S, Alswaitti M, Mirjalili S, Idris N, Ismail MA, Omar MS (2021) Dynamic salp swarm algorithm for feature selection. Expert Syst Appl 164:113873","journal-title":"Expert Syst Appl"},{"key":"10155_CR6","volume":"117","author":"J Xie","year":"2023","unstructured":"Xie J, Sage M, Zhao YF (2023) Feature selection and feature learning in machine learning applications for gas turbines: A review. Eng Appl Artif Intell 117:105591","journal-title":"Eng Appl Artif Intell"},{"key":"10155_CR7","doi-asserted-by":"crossref","first-page":"12201","DOI":"10.1007\/s00521-019-04368-6","volume":"32","author":"H Chantar","year":"2020","unstructured":"Chantar H, Mafarja M, Alsawalqah H, Heidari AA, Aljarah I, Faris H (2020) Feature selection using binary grey wolf optimizer with elite-based crossover for Arabic text classification. Neural Comput Appl 32:12201\u201312220","journal-title":"Neural Comput Appl"},{"key":"10155_CR8","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.110521","volume":"269","author":"R Sheikhpour","year":"2023","unstructured":"Sheikhpour R, Berahmand K, Forouzandeh S (2023) Hessian-based semi-supervised feature selection using generalized uncorrelated constraint. Knowl-Based Syst 269:110521","journal-title":"Knowl-Based Syst"},{"key":"10155_CR9","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1007\/s11831-020-09412-6","volume":"28","author":"M Sharma","year":"2021","unstructured":"Sharma M, Kaur P (2021) A comprehensive analysis of nature-inspired meta-heuristic techniques for feature selection problem. Archives of Computational Methods in Engineering 28:1103\u20131127","journal-title":"Archives of Computational Methods in Engineering"},{"key":"10155_CR10","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.neucom.2015.06.083","volume":"172","author":"E Emary","year":"2016","unstructured":"Emary E, Zawbaa HM, Hassanien AE (2016) Binary grey wolf optimization approaches for feature selection. Neurocomputing 172:371\u2013381","journal-title":"Neurocomputing"},{"key":"10155_CR11","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113364","volume":"152","author":"N Neggaz","year":"2020","unstructured":"Neggaz N, Houssein EH, Hussain K (2020) An efficient henry gas solubility optimization for feature selection. Expert Syst Appl 152:113364","journal-title":"Expert Syst Appl"},{"key":"10155_CR12","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113249","volume":"148","author":"H Alazzam","year":"2020","unstructured":"Alazzam H, Sharieh A, Sabri KE (2020) A feature selection algorithm for intrusion detection system based on pigeon inspired optimizer. Expert Syst Appl 148:113249","journal-title":"Expert Syst Appl"},{"key":"10155_CR13","doi-asserted-by":"crossref","first-page":"3741","DOI":"10.1007\/s00366-020-01028-5","volume":"37","author":"Y Zhang","year":"2021","unstructured":"Zhang Y, Liu R, Wang X, Chen H, Li C (2021) Boosted binary Harris hawks optimizer and feature selection. Engineering with Computers 37:3741\u20133770","journal-title":"Engineering with Computers"},{"issue":"5","key":"10155_CR14","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1109\/TEVC.2020.2968743","volume":"24","author":"XF Song","year":"2020","unstructured":"Song XF, Zhang Y, Guo YN, Sun XY, Wang YL (2020) Variable-size cooperativecoevolutionaryy particle swarm optimization for feature selection on high-dimensional data. IEEE Trans Evol Comput 24(5):882\u2013895","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"10155_CR15","doi-asserted-by":"crossref","first-page":"1656","DOI":"10.1109\/TSMCB.2012.2227469","volume":"43","author":"B Xue","year":"2012","unstructured":"Xue B, Zhang M, Browne WN (2012) Particle swarm optimization for feature selection in classification: A multi-objective approach. IEEE transactions on cybernetics 43(6):1656\u20131671","journal-title":"IEEE transactions on cybernetics"},{"key":"10155_CR16","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106560","volume":"211","author":"G Dhiman","year":"2021","unstructured":"Dhiman G, Oliva D, Kaur A, Singh KK, Vimal S, Sharma A, Cengiz K (2021) BEPO: A novel binary emperor penguin optimizer for automatic feature selection. Knowl-Based Syst 211:106560","journal-title":"Knowl-Based Syst"},{"key":"10155_CR17","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2019.105285","volume":"192","author":"M Paniri","year":"2020","unstructured":"Paniri M, Dowlatshahi MB, Nezamabadi-Pour H (2020) MLACO: A multi-label feature selection algorithm based on ant colony optimization. Knowl-Based Syst 192:105285","journal-title":"Knowl-Based Syst"},{"key":"10155_CR18","volume":"195","author":"P Hu","year":"2020","unstructured":"Hu P, Pan JS, Chu SC (2020) Improved binary grey wolf optimizer and its application for feature selection. Knowl-Based Syst 195:105746","journal-title":"Knowl-Based Syst"},{"key":"10155_CR19","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.knosys.2018.08.003","volume":"161","author":"M Mafarja","year":"2018","unstructured":"Mafarja M, Aljarah I, Heidari AA, Faris H, Fournier-Viger P, Li X, Mirjalili S (2018) Binary dragonfly optimization for feature selection using time-varying transfer functions. Knowl-Based Syst 161:185\u2013204","journal-title":"Knowl-Based Syst"},{"key":"10155_CR20","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106131","volume":"203","author":"AI Hammouri","year":"2020","unstructured":"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","journal-title":"Knowl-Based Syst"},{"key":"10155_CR21","volume":"107","author":"RCT de Souza","year":"2020","unstructured":"de Souza RCT, de Macedo CA, dos Santos Coelho L, Pierezan J, Mariani VC (2020) Binary coyote optimization algorithm for feature selection. Pattern Recogn 107:107470","journal-title":"Pattern Recogn"},{"key":"10155_CR22","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.ins.2019.05.038","volume":"497","author":"M Taradeh","year":"2019","unstructured":"Taradeh M, Mafarja M, Heidari AA, Faris H, Aljarah I, Mirjalili S, Fujita H (2019) An evolutionary gravitational search-based feature selection. Inf Sci 497:219\u2013239","journal-title":"Inf Sci"},{"key":"10155_CR23","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2019.113103","volume":"145","author":"N Neggaz","year":"2020","unstructured":"Neggaz N, Ewees AA, Abd Elaziz M, Mafarja M (2020) Boosting salp swarm algorithm by sine cosine algorithm and disrupt operator for feature selection. Expert Syst Appl 145:113103","journal-title":"Expert Syst Appl"},{"key":"10155_CR24","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.123362","volume":"248","author":"BD Kwakye","year":"2024","unstructured":"Kwakye BD, Li Y, Mohamed HH, Baidoo E, Asenso TQ (2024) Particle guided metaheuristic algorithm for global optimization and feature selection problems. Expert Syst Appl 248:123362","journal-title":"Expert Syst Appl"},{"key":"10155_CR25","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.cirpj.2024.01.004","volume":"50","author":"S Gaugel","year":"2024","unstructured":"Gaugel S, Reichert M (2024) Data-driven multi-objective optimization of hydraulic pump test cycles via wrapper feature selection. CIRP J Manuf Sci Technol 50:14\u201325","journal-title":"CIRP J Manuf Sci Technol"},{"key":"10155_CR26","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.123337","volume":"247","author":"S Tijjani","year":"2024","unstructured":"Tijjani S, Ab Wahab MN, Noor MHM (2024) An enhanced particle swarm optimization with position update for optimal feature selection. Expert Syst Appl 247:123337","journal-title":"Expert Syst Appl"},{"key":"10155_CR27","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.knosys.2019.02.010","volume":"172","author":"M Abd Elaziz","year":"2019","unstructured":"Abd Elaziz M, Mirjalili S (2019) A hyper-heuristic for improving the initial population of whale optimization algorithm. Knowl-Based Syst 172:42\u201363","journal-title":"Knowl-Based Syst"},{"key":"10155_CR28","volume":"46","author":"XS Yang","year":"2020","unstructured":"Yang XS (2020) Nature-inspired optimization algorithms: Challenges and open problems. Journal of Computational Science 46:101104","journal-title":"Journal of Computational Science"},{"key":"10155_CR29","volume-title":"Nature-inspired optimization algorithms","author":"XS Yang","year":"2020","unstructured":"Yang XS (2020) Nature-inspired optimization algorithms. Academic Press"},{"key":"10155_CR30","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1023\/A:1021251113462","volume":"115","author":"YC Ho","year":"2002","unstructured":"Ho YC, Pepyne DL (2002) Simple explanation of the no-free-lunch theorem and its implications. J Optim Theory Appl 115:549\u2013570","journal-title":"J Optim Theory Appl"},{"key":"10155_CR31","volume":"170","author":"JLJ Pereira","year":"2021","unstructured":"Pereira JLJ, Francisco MB, Diniz CA, Oliver GA, Cunha SS Jr, Gomes GF (2021) Lichtenberg algorithm: A novel hybrid physics-based meta-heuristic for global optimization. Expert Syst Appl 170:114522","journal-title":"Expert Syst Appl"},{"issue":"19","key":"10155_CR32","doi-asserted-by":"crossref","first-page":"1400","DOI":"10.1103\/PhysRevLett.47.1400","volume":"47","author":"TA Witten Jr","year":"1981","unstructured":"Witten TA Jr, Sander LM (1981) Diffusion-limited aggregation, a kinetic critical phenomenon. Phys Rev Lett 47(19):1400","journal-title":"Phys Rev Lett"},{"issue":"9","key":"10155_CR33","doi-asserted-by":"crossref","first-page":"5686","DOI":"10.1103\/PhysRevB.27.5686","volume":"27","author":"TA Witten","year":"1983","unstructured":"Witten TA, Sander LM (1983) Diffusion-limited aggregation. Phys Rev B 27(9):5686","journal-title":"Phys Rev B"},{"issue":"1","key":"10155_CR34","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1108\/EC-12-2019-0564","volume":"38","author":"JLJ Pereira","year":"2021","unstructured":"Pereira JLJ, Chuman M, Cunha SS Jr, Gomes GF (2021) Lichtenberg optimization algorithm applied to crack tip identification in thin plate-like structures. Eng Comput 38(1):151\u2013166","journal-title":"Eng Comput"},{"key":"10155_CR35","volume":"97","author":"JLJ Pereira","year":"2021","unstructured":"Pereira JLJ, Francisco MB, da Cunha Jr SS, Gomes GF (2021) A powerful Lichtenberg Optimization Algorithm: A damage identification case study. Eng Appl Artif Intell 97:104055","journal-title":"Eng Appl Artif Intell"},{"issue":"11","key":"10155_CR36","doi-asserted-by":"crossref","first-page":"1922","DOI":"10.1080\/0305215X.2020.1839442","volume":"53","author":"MB Francisco","year":"2021","unstructured":"Francisco MB, Junqueira DM, Oliver GA, Pereira JLJ, da Cunha Jr Jr, S.S. and Gomes, G.F. (2021) Design optimizations of carbon fibre reinforced polymer isogrid lower limb prosthesis using particle swarm optimization and Lichtenberg algorithm. Eng Optim 53(11):1922\u20131945","journal-title":"Eng Optim"},{"issue":"6","key":"10155_CR37","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1108\/EC-04-2020-0222","volume":"38","author":"M Francisco","year":"2021","unstructured":"Francisco M, Roque L, Pereira J, Machado S, da Cunha Jr SS, Gomes GF (2021) A statistical analysis of high-performance prosthetic isogrid composite tubes using response surface method. Eng Comput 38(6):2481\u20132504","journal-title":"Eng Comput"},{"issue":"15","key":"10155_CR38","doi-asserted-by":"crossref","first-page":"7195","DOI":"10.1007\/s00500-022-07105-9","volume":"26","author":"JLJ Pereira","year":"2022","unstructured":"Pereira JLJ, Francisco MB, Ribeiro RF, Cunha SS, Gomes GF (2022) Deep multi-objective design optimization of CFRP isogrid tubes using lichtenberg algorithm. Soft Comput 26(15):7195\u20137209","journal-title":"Soft Comput"},{"key":"10155_CR39","volume":"187","author":"JLJ Pereira","year":"2022","unstructured":"Pereira JLJ, Oliver GA, Francisco MB, Cunha SS Jr, Gomes GF (2022) Multi-objective lichtenberg algorithm: A hybrid physics-based meta-heuristic for solving engineering problems. Expert Syst Appl 187:115939","journal-title":"Expert Syst Appl"},{"issue":"4","key":"10155_CR40","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1080\/15435075.2022.2050375","volume":"20","author":"TAZ De Souza","year":"2023","unstructured":"De Souza TAZ, Pereira JLJ, Francisco MB, Sotomonte CAR, Jun Ma B, Gomes GF, Coronado CJR (2023) Multi-objective optimization for methane, glycerol, and ethanol steam reforming using lichtenberg algorithm. Int J Green Energy 20(4):390\u2013407","journal-title":"Int J Green Energy"},{"key":"10155_CR41","first-page":"1346","volume":"50","author":"M Challan","year":"2022","unstructured":"Challan M, Jeet S, Bagal DK, Mishra L, Pattanaik AK, Barua A (2022) Fabrication and mechanical characterization of red mud based Al2025-T6 MMC using Lichtenberg optimization algorithm and Whale optimization algorithm. Materials Today: Proceedings 50:1346\u20131353","journal-title":"Materials Today: Proceedings"},{"key":"10155_CR42","first-page":"893","volume":"50","author":"A Mohanty","year":"2022","unstructured":"Mohanty A, Nag KS, Bagal DK, Barua A, Jeet S, Mahapatra SS, Cherkia H (2022) Parametric optimization of parameters affecting dimension precision of FDM printed part using hybrid Taguchi-MARCOS-nature inspired heuristic optimization technique. Materials Today: Proceedings 50:893\u2013903","journal-title":"Materials Today: Proceedings"},{"key":"10155_CR43","volume":"254","author":"Z Tian","year":"2022","unstructured":"Tian Z, Wang J (2022) Variable frequency wind speed trend prediction system based on combined neural network and improved multi-objective optimization algorithm. Energy 254:124249","journal-title":"Energy"},{"key":"10155_CR44","volume":"180","author":"JLJ Pereira","year":"2022","unstructured":"Pereira JLJ, Francisco MB, de Oliveira LA, Chaves JAS, Cunha SS Jr, Gomes GF (2022) Multi-objective sensor placement optimization of helicopter rotor blade based on Feature Selection. Mech Syst Signal Process 180:109466","journal-title":"Mech Syst Signal Process"},{"issue":"5","key":"10155_CR45","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1080\/00029890.1961.11989696","volume":"68","author":"AF Horadam","year":"1961","unstructured":"Horadam AF (1961) A generalized Fibonacci sequence. Am Math Mon 68(5):455\u2013459","journal-title":"Am Math Mon"},{"issue":"3","key":"10155_CR46","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1090\/S0002-9939-1953-0055639-3","volume":"4","author":"J Kiefer","year":"1953","unstructured":"Kiefer J (1953) Sequential minimax search for a maximum. Proceedings of the American mathematical society 4(3):502\u2013506","journal-title":"Proceedings of the American mathematical society"},{"key":"10155_CR47","doi-asserted-by":"crossref","first-page":"9425","DOI":"10.1007\/s00521-021-05703-6","volume":"33","author":"F Keshavarz-Ghorbani","year":"2021","unstructured":"Keshavarz-Ghorbani F, Pasandideh SHR (2021) Optimizing a two-level closed-loop supply chain under the vendor managed inventory contract and learning: Fibonacci, GA, IWO, MFO algorithms. Neural Comput Appl 33:9425\u20139450","journal-title":"Neural Comput Appl"},{"key":"10155_CR48","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.isatra.2020.05.022","volume":"104","author":"D Horla","year":"2020","unstructured":"Horla D, Sadalla T (2020) Optimal tuning of fractional-order controllers based on Fibonacci-search method. ISA Trans 104:287\u2013298","journal-title":"ISA Trans"},{"issue":"2","key":"10155_CR49","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1007\/s00500-019-03949-w","volume":"24","author":"AF Nematollahi","year":"2020","unstructured":"Nematollahi AF, Rahiminejad A, Vahidi B (2020) A novel meta-heuristic optimization method based on golden ratio in nature. Soft Comput 24(2):1117\u20131151","journal-title":"Soft Comput"},{"key":"10155_CR50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.engappai.2018.04.012","volume":"74","author":"A Etminaniesfahani","year":"2018","unstructured":"Etminaniesfahani A, Ghanbarzadeh A, Marashi Z (2018) Fibonacci indicator algorithm: A novel tool for complex optimization problems. Eng Appl Artif Intell 74:1\u20139","journal-title":"Eng Appl Artif Intell"},{"issue":"19","key":"10155_CR51","doi-asserted-by":"crossref","first-page":"9709","DOI":"10.3390\/app12199709","volume":"12","author":"P Yuan","year":"2022","unstructured":"Yuan P, Zhang T, Yao L, Lu Y, Zhuang W (2022) A hybrid golden jackal optimization and golden sine algorithm with dynamic lens-imaging learning for global optimization problems. Appl Sci 12(19):9709","journal-title":"Appl Sci"},{"key":"10155_CR52","doi-asserted-by":"crossref","DOI":"10.1016\/j.jocs.2022.101651","volume":"61","author":"A Etminaniesfahani","year":"2022","unstructured":"Etminaniesfahani A, Gu H, Salehipour A (2022) ABFIA: A hybrid algorithm based on artificial bee colony and Fibonacci indicator algorithm. Journal of Computational Science 61:101651","journal-title":"Journal of Computational Science"},{"key":"10155_CR53","doi-asserted-by":"crossref","unstructured":"Sahoo, S.K., Reang, S., Saha, A.K. and Chakraborty, S., 2024. F-WOA: an improved whale optimization algorithm based on Fibonacci search principle for global optimization. In\u00a0Handbook of Whale Optimization Algorithm Academic Press. 217\u2013233","DOI":"10.1016\/B978-0-32-395365-8.00022-1"},{"key":"10155_CR54","volume":"227","author":"SK Sahoo","year":"2023","unstructured":"Sahoo SK, Houssein EH, Premkumar M, Saha AK, Emam MM (2023) Self-adaptive moth flame optimizer combined with crossover operator and Fibonacci search strategy for COVID-19 CT image segmentation. Expert Syst Appl 227:120367","journal-title":"Expert Syst Appl"},{"issue":"1","key":"10155_CR55","doi-asserted-by":"crossref","first-page":"2298764","DOI":"10.1080\/23311916.2023.2298764","volume":"11","author":"N Hartono","year":"2024","unstructured":"Hartono N, Pham DT (2024) A novel Fibonacci-inspired enhancement of the Bees Algorithm: application to robotic disassembly sequence planning. Cogent Engineering 11(1):2298764","journal-title":"Cogent Engineering"},{"key":"10155_CR56","doi-asserted-by":"crossref","unstructured":"Mukherjee, D.S. and Yeri, N.G., 2021, December. Investigation of weight initialization using Fibonacci Sequence on the performance of neural networks. In\u00a02021 IEEE Pune Section International Conference (PuneCon)\u00a0(pp. 1\u20138). IEEE.","DOI":"10.1109\/PuneCon52575.2021.9686532"},{"issue":"17","key":"10155_CR57","doi-asserted-by":"crossref","first-page":"14463","DOI":"10.1007\/s00521-022-07261-x","volume":"34","author":"A Garain","year":"2022","unstructured":"Garain A, Ray B, Giampaolo F, Velasquez JD, Singh PK, Sarkar R (2022) GRaNN: feature selection with golden ratio-aided neural network for emotion, gender and speaker identification from voice signals. Neural Comput Appl 34(17):14463\u201314486","journal-title":"Neural Comput Appl"},{"key":"10155_CR58","doi-asserted-by":"crossref","DOI":"10.1016\/j.compeleceng.2024.109234","volume":"117","author":"S Dincer","year":"2024","unstructured":"Dincer S, Ulutas G, Ustubioglu B, Tahaoglu G, Sklavos N (2024) Golden ratio based deep fake video detection system with fusion of capsule networks. Comput Electr Eng 117:109234","journal-title":"Comput Electr Eng"},{"key":"10155_CR59","unstructured":"Asuncion, A. and Newman, D., 2007. UCI machine learning repository."},{"key":"10155_CR60","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1007\/s00521-015-1920-1","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput Appl 27:1053\u20131073","journal-title":"Neural Comput Appl"},{"issue":"3","key":"10155_CR61","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/00031305.1992.10475879","volume":"46","author":"NS Altman","year":"1992","unstructured":"Altman NS (1992) An introduction to kernel and nearest-neighbor nonparametric regression. Am Stat 46(3):175\u2013185","journal-title":"Am Stat"},{"issue":"4","key":"10155_CR62","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.patrec.2006.08.016","volume":"28","author":"MA Tahir","year":"2007","unstructured":"Tahir MA, Bouridane A, Kurugollu F (2007) Simultaneous feature selection and feature weighting using Hybrid Tabu Search\/K-nearest neighbor classifier. Pattern Recogn Lett 28(4):438\u2013446","journal-title":"Pattern Recogn Lett"},{"key":"10155_CR63","doi-asserted-by":"crossref","first-page":"3462","DOI":"10.1007\/s10489-018-1158-6","volume":"48","author":"GI Sayed","year":"2018","unstructured":"Sayed GI, Khoriba G, Haggag MH (2018) A novel chaotic salp swarm algorithm for global optimization and feature selection. Appl Intell 48:3462\u20133481","journal-title":"Appl Intell"},{"key":"10155_CR64","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.asoc.2017.11.006","volume":"62","author":"M Mafarja","year":"2018","unstructured":"Mafarja M, andMirjalili. MS (2018) Whale optimization approaches for wrapper feature selection. Appl Soft Comput 62:441\u2013453","journal-title":"Appl Soft Comput"},{"key":"10155_CR65","unstructured":"Alweshah, M., Khalaileh, S.A., Gupta, B.B., Almomani, A., Hammouri, A.I. and Al-Betar, M.A., 2022. The monarch butterfly optimization algorithm for solving feature selection problems.\u00a0Neural Computing and Applications, pp.1\u201315."},{"key":"10155_CR66","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.neucom.2022.04.083","volume":"494","author":"T Dokeroglu","year":"2022","unstructured":"Dokeroglu T, Deniz A, Kiziloz HE (2022) A comprehensive survey on recent metaheuristics for feature selection. Neurocomputing 494:269\u2013296","journal-title":"Neurocomputing"},{"key":"10155_CR67","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.knosys.2018.12.031","volume":"168","author":"M Wang","year":"2019","unstructured":"Wang M, Wu C, Wang L, Xiang D, Huang X (2019) A feature selection approach for hyperspectral image based on modified ant lion optimizer. Knowl-Based Syst 168:39\u201348","journal-title":"Knowl-Based Syst"},{"key":"10155_CR68","volume":"66","author":"JM Cruz-Duarte","year":"2021","unstructured":"Cruz-Duarte JM, Amaya I, Ortiz-Bayliss JC, Conant-Pablos SE, Terashima-Mar\u00edn H, Shi Y (2021) Hyper-heuristics to customise metaheuristics for continuous optimisation. Swarm Evol Comput 66:100935","journal-title":"Swarm Evol Comput"},{"key":"10155_CR69","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1016\/j.asoc.2018.10.036","volume":"74","author":"H Rao","year":"2019","unstructured":"Rao H, Shi X, Rodrigue AK, Feng J, Xia Y, Elhoseny M, Yuan X, Gu L (2019) Feature selection based on artificial bee colony and gradient boosting decision tree. Appl Soft Comput 74:634\u2013642","journal-title":"Appl Soft Comput"},{"issue":"5","key":"10155_CR70","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0196707","volume":"13","author":"E Hamouda","year":"2018","unstructured":"Hamouda E, El-Metwally S, Tarek M (2018) Ant Lion Optimization algorithm for kidney exchanges. PLoS ONE 13(5):e0196707","journal-title":"PLoS ONE"},{"key":"10155_CR71","doi-asserted-by":"crossref","unstructured":"Yang, C.S., Chuang, L.Y., Ke, C.H. and Yang, C.H., 2008, June. Boolean binary particle swarm optimization for feature selection. In\u00a02008 IEEE congress on evolutionary computation (IEEE world congress on computational intelligence)\u00a0(pp. 2093\u20132098). IEEE.","DOI":"10.1109\/CEC.2008.4631076"},{"key":"10155_CR72","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.knosys.2018.03.031","volume":"151","author":"X Zhang","year":"2018","unstructured":"Zhang X, Mei C, Chen D, Yang Y (2018) A fuzzy rough set-based feature selection method using representative instances. Knowl-Based Syst 151:216\u2013229","journal-title":"Knowl-Based Syst"},{"key":"10155_CR73","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.cie.2017.10.025","volume":"115","author":"D Zouache","year":"2018","unstructured":"Zouache D, Abdelaziz FB (2018) A cooperative swarm intelligence algorithm based on quantum-inspired and rough sets for feature selection. Comput Ind Eng 115:26\u201336","journal-title":"Comput Ind Eng"},{"key":"10155_CR74","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.110462","volume":"269","author":"RR Mostafa","year":"2023","unstructured":"Mostafa RR, Gaheen MA, Abd ElAziz M, Al-Betar MA, Ewees AA (2023) An improved gorilla troops optimizer for global optimization problems and feature selection. Knowl-Based Syst 269:110462","journal-title":"Knowl-Based Syst"},{"key":"10155_CR75","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.swevo.2012.09.002","volume":"9","author":"S Mirjalili","year":"2013","unstructured":"Mirjalili S, Lewis A (2013) S-shaped versus V-shaped transfer functions for binary particle swarm optimization. Swarm Evol Comput 9:1\u201314","journal-title":"Swarm Evol Comput"},{"issue":"17","key":"10155_CR76","doi-asserted-by":"crossref","first-page":"11027","DOI":"10.1007\/s00521-020-05560-9","volume":"33","author":"KK Ghosh","year":"2021","unstructured":"Ghosh KK, Guha R, Bera SK, Kumar N, Sarkar R (2021) S-shaped versus V-shaped transfer functions for binary Manta ray foraging optimization in feature selection problem. Neural Comput Appl 33(17):11027\u201311041","journal-title":"Neural Comput Appl"},{"key":"10155_CR77","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1007\/s00521-014-1743-5","volume":"26","author":"S Saremi","year":"2015","unstructured":"Saremi S, Mirjalili S, Lewis A (2015) How important is a transfer function in discrete heuristic algorithms. Neural Comput Appl 26:625\u2013640","journal-title":"Neural Comput Appl"},{"key":"10155_CR78","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1016\/j.istruc.2022.09.091","volume":"45","author":"MB Francisco","year":"2022","unstructured":"Francisco MB, Pereira JLJ, Vasconcelos GAVB, da Cunha Jr SS, Gomes GF (2022) November. Multi-objective design optimization of double arrowhead auxetic model using Lichtenberg algorithm based on metamodelling. Structures 45:1199\u20131211","journal-title":"Structures"},{"issue":"12","key":"10155_CR79","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1063\/1.1707274","volume":"10","author":"FH Merrill","year":"1939","unstructured":"Merrill FH, Von Hippel A (1939) The atomphysical interpretation of Lichtenberg figures and their application to the study of gas discharge phenomena. J Appl Phys 10(12):873\u2013887","journal-title":"J Appl Phys"},{"issue":"21","key":"10155_CR80","doi-asserted-by":"crossref","first-page":"15619","DOI":"10.1007\/s00500-023-08782-w","volume":"27","author":"JLJ Pereira","year":"2023","unstructured":"Pereira JLJ, Francisco MB, de Almeida FA, Ma BJ, Cunha SS Jr, Gomes GF (2023) Enhanced Lichtenberg algorithm: a discussion on improving meta-heuristics. Soft Comput 27(21):15619\u201315647","journal-title":"Soft Comput"},{"key":"10155_CR81","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.H. and Friedman, J.H., 2009.\u00a0The elements of statistical learning: data mining, inference, and prediction\u00a0(Vol. 2, pp. 1\u2013758). New York: springer.","DOI":"10.1007\/b94608_8"},{"key":"10155_CR82","doi-asserted-by":"crossref","unstructured":"Bello, R., Gomez, Y., Nowe, A. and Garcia, M.M., 2007, October. Two-step particle swarm optimization to solve the feature selection problem. In\u00a0Seventh international conference on intelligent systems design and applications (ISDA 2007)(pp. 691\u2013696). IEEE.","DOI":"10.1109\/ISDA.2007.101"},{"issue":"17","key":"10155_CR83","doi-asserted-by":"crossref","first-page":"2914","DOI":"10.1016\/j.neucom.2011.03.034","volume":"74","author":"MM Kabir","year":"2011","unstructured":"Kabir MM, Shahjahan M, Murase K (2011) A new local search based hybrid genetic algorithm for feature selection. Neurocomputing 74(17):2914\u20132928","journal-title":"Neurocomputing"},{"key":"10155_CR84","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2020.106628","volume":"147","author":"I Aljarah","year":"2020","unstructured":"Aljarah I, Habib M, Faris H, Al-Madi N, Heidari AA, Mafarja M, Abd Elaziz M, Mirjalili S (2020) A dynamic locality multi-objective salp swarm algorithm for feature selection. Comput Ind Eng 147:106628","journal-title":"Comput Ind Eng"},{"issue":"1","key":"10155_CR85","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1007\/s10462-020-09860-3","volume":"54","author":"M Abdel-Basset","year":"2021","unstructured":"Abdel-Basset M, Ding W, El-Shahat D (2021) A hybrid Harris Hawks optimization algorithm with simulated annealing for feature selection. Artif Intell Rev 54(1):593\u2013637","journal-title":"Artif Intell Rev"},{"issue":"1","key":"10155_CR86","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u00eda 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\u201318","journal-title":"Swarm Evol Comput"},{"issue":"4","key":"10155_CR87","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.jclinepi.2007.04.021","volume":"61","author":"MJ Saary","year":"2008","unstructured":"Saary MJ (2008) Radar plots: a useful way for presenting multivariate health care data. J Clin Epidemiol 61(4):311\u2013317","journal-title":"J Clin Epidemiol"},{"key":"10155_CR88","doi-asserted-by":"crossref","DOI":"10.1016\/j.chemolab.2020.104170","volume":"206","author":"ZY Algamal","year":"2020","unstructured":"Algamal ZY, Qasim MK, Lee MH, Ali HTM (2020) High-dimensional QSAR\/QSPR classification modeling based on improving pigeon optimization algorithm. Chemom Intell Lab Syst 206:104170","journal-title":"Chemom Intell Lab Syst"},{"key":"10155_CR89","volume":"212","author":"NA Al-Thanoon","year":"2021","unstructured":"Al-Thanoon NA, Algamal ZY, Qasim OS (2021) Feature selection based on a crow search algorithm for big data classification. Chemom Intell Lab Syst 212:104288","journal-title":"Chemom Intell Lab Syst"},{"issue":"1","key":"10155_CR90","first-page":"20220228","volume":"32","author":"ZA Hamed Alnaish","year":"2023","unstructured":"Hamed Alnaish ZA, Algamal ZY (2023) Improving binary crow search algorithm for feature selection. J Intell Syst 32(1):20220228","journal-title":"J Intell Syst"},{"issue":"4","key":"10155_CR91","doi-asserted-by":"crossref","first-page":"3307","DOI":"10.1007\/s00521-022-07852-8","volume":"35","author":"AA Ewees","year":"2023","unstructured":"Ewees AA, Al-Qaness MA, Abualigah L, Algamal ZY, Oliva D, Yousri D, Elaziz MA (2023) Enhanced feature selection technique using slime mould algorithm: A case study on chemical data. Neural Comput Appl 35(4):3307\u20133324","journal-title":"Neural Comput Appl"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10155-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10155-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10155-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,28]],"date-time":"2024-09-28T08:11:43Z","timestamp":1727511103000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10155-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,13]]},"references-count":91,"journal-issue":{"issue":"32","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["10155"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10155-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,13]]},"assertion":[{"value":"1 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 June 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 August 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}