{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T12:49:46Z","timestamp":1777553386804,"version":"3.51.4"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:00:00Z","timestamp":1695340800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:00:00Z","timestamp":1695340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-16890-w","type":"journal-article","created":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T07:01:59Z","timestamp":1695366119000},"page":"32613-32653","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems"],"prefix":"10.1007","volume":"83","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2203-4549","authenticated-orcid":false,"given":"Laith","family":"Abualigah","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diego","family":"Oliva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heming","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Faiza","family":"Gul","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nima","family":"Khodadadi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdelazim G","family":"Hussien","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad Al","family":"Shinwan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Absalom E.","family":"Ezugwu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Belal","family":"Abuhaija","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raed Abu","family":"Zitar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,22]]},"reference":[{"key":"16890_CR1","unstructured":"Soerensen JS, Johannesen L, Grove USL, Lundhus K, Couderc J-P, Graff C (2010) A comparison of iir and wavelet filtering for noise reduction of the ecg. In: 2010 computing in cardiology, IEEE, pp 489\u2013492"},{"issue":"18","key":"16890_CR2","doi-asserted-by":"crossref","first-page":"2230","DOI":"10.3390\/math9182230","volume":"9","author":"Y Liao","year":"2021","unstructured":"Liao Y, Zhao W, Wang L (2021) Improved manta ray foraging optimization for parameters identification of magnetorheological dampers. Mathematics 9(18):2230","journal-title":"Mathematics"},{"issue":"6","key":"16890_CR3","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1080\/0305215X.2019.1624740","volume":"52","author":"AG Hussien","year":"2020","unstructured":"Hussien AG, Hassanien AE, Houssein EH, Amin M, Azar AT (2020) New binary whale optimization algorithm for discrete optimization problems. Eng Optim 52(6):945\u2013959","journal-title":"Eng Optim"},{"issue":"1","key":"16890_CR4","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s12652-021-02892-9","volume":"13","author":"AG Hussien","year":"2022","unstructured":"Hussien AG (2022) An enhanced opposition-based salp swarm algorithm for global optimization and engineering problems. J Ambient Intell Human Comput 13(1):129\u2013150","journal-title":"J Ambient Intell Human Comput"},{"key":"16890_CR5","doi-asserted-by":"crossref","unstructured":"Hussien AG, Hassanien AE, Houssein EH, Bhattacharyya S, Amin M (2019) S-shaped binary whale optimization algorithm for feature selection. In: Recent trends in signal and image processing, Springer, pp 79\u201387","DOI":"10.1007\/978-981-10-8863-6_9"},{"key":"16890_CR6","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1016\/j.asoc.2015.09.007","volume":"37","author":"G Wu","year":"2015","unstructured":"Wu G, Pedrycz W, Suganthan PN, Mallipeddi R (2015) A variable reduction strategy for evolutionary algorithms handling equality constraints. Appl Soft Comput 37:774\u2013786","journal-title":"Appl Soft Comput"},{"key":"16890_CR7","doi-asserted-by":"crossref","unstructured":"Mostafa RR, Hussien AG, Khan MA, Kadry S, Hashim FA (2022) Enhanced coot optimization algorithm for dimensionality reduction. In: 2022 Fifth international conference of women in data science at prince sultan university (WiDS PSU), IEEE, pp 43\u201348","DOI":"10.1109\/WiDS-PSU54548.2022.00020"},{"key":"16890_CR8","doi-asserted-by":"crossref","unstructured":"Abualigah L, Gandomi AH, Elaziz MA, Hussien AG, Khasawneh AM, Alshinwan M, Houssein EH (2020) Nature-inspired optimization algorithms for text document clustering\u2014a comprehensive analysis. Algorithms 13(12):345","DOI":"10.3390\/a13120345"},{"key":"16890_CR9","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.116895","volume":"198","author":"MH Nadimi-Shahraki","year":"2022","unstructured":"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","journal-title":"Expert Syst Appl"},{"key":"16890_CR10","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2021.107389","volume":"107","author":"B Morales-Castaneda","year":"2021","unstructured":"Morales-Castaneda B, Zaldivar D, Cuevas E, Rodriguez A, Navarro MA (2021) Population management in metaheuristic algorithms: Could less be more? Appl Soft Comput 107:107389","journal-title":"Appl Soft Comput"},{"key":"16890_CR11","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.swevo.2015.05.002","volume":"24","author":"N Lynn","year":"2015","unstructured":"Lynn N, Suganthan PN (2015) Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation. Swarm Evol Comput 24:11\u201324","journal-title":"Swarm Evol Comput"},{"issue":"2","key":"16890_CR12","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1007\/s13042-021-01326-4","volume":"13","author":"AG Hussien","year":"2022","unstructured":"Hussien AG, Amin M (2022) A self-adaptive harris hawks optimization algorithm with opposition-based learning and chaotic local search strategy for global optimization and feature selection. Int J Mach Learn Cyber 13(2):309\u2013336","journal-title":"Int J Mach Learn Cyber"},{"key":"16890_CR13","doi-asserted-by":"crossref","unstructured":"Fathi H, AlSalman H, Gumaei A, Manhrawy II, Hussien AG, El-Kafrawy P (2021) An efficient cancer classification model using microarray and high-dimensional data. Comput Intell Neurosci","DOI":"10.1155\/2021\/7231126"},{"key":"16890_CR14","doi-asserted-by":"crossref","unstructured":"Navarro MA, Ramos-Michel A, Gaspar A, Oliva D, Hinojosa S, Mousavirad SJ, P\u00e9rez-Cisneros M (2022) Improving the convergence and diversity in differential evolution through a stock market criterion. In: International conference on the applications of evolutionary computation (Part of EvoStar), Springer, pp 157\u2013172","DOI":"10.1007\/978-3-031-02462-7_11"},{"key":"16890_CR15","doi-asserted-by":"crossref","unstructured":"Hussien AG, Abualigah L, Abu\u00a0Zitar R, Hashim FA, Amin M, Saber A, Almotairi KH, Gandomi AH (2022) Recent advances in harris hawks optimization: A comparative study and applications. Electronics 11(12):1919","DOI":"10.3390\/electronics11121919"},{"key":"16890_CR16","doi-asserted-by":"crossref","unstructured":"Hussien AG, Oliva D, Houssein EH, Juan AA, Yu X (2020) Binary whale optimization algorithm for dimensionality reduction. Mathematics 8(10):1821","DOI":"10.3390\/math8101821"},{"key":"16890_CR17","doi-asserted-by":"crossref","first-page":"77746","DOI":"10.1109\/ACCESS.2020.2990338","volume":"8","author":"AS Assiri","year":"2020","unstructured":"Assiri AS, Hussien AG, Amin M (2020) Ant lion optimization: variants, hybrids, and applications. IEEE Access 8:77746\u201377764","journal-title":"IEEE Access"},{"key":"16890_CR18","doi-asserted-by":"crossref","unstructured":"Singh S, Singh H, Mittal N, Hussien AG , Sroubek F (2022) A feature level image fusion for night-vision context enhancement using arithmetic optimization algorithm based image segmentation. Expert Syst Appl 118272","DOI":"10.1016\/j.eswa.2022.118272"},{"key":"16890_CR19","doi-asserted-by":"crossref","unstructured":"Hussien AG, Hassanien AE, Houssein EH (2017) Swarming behaviour of salps algorithm for predicting chemical compound activities. In: 2017 eighth international conference on intelligent computing and information systems (ICICIS), IEEE, pp 315\u2013320","DOI":"10.1109\/INTELCIS.2017.8260072"},{"key":"16890_CR20","doi-asserted-by":"crossref","unstructured":"Hussien AG, Houssein EH, Hassanien AE (2017) A binary whale optimization algorithm with hyperbolic tangent fitness function for feature selection. In: 2017 Eighth international conference on intelligent computing and information systems (ICICIS), IEEE, pp 166\u2013172","DOI":"10.1109\/INTELCIS.2017.8260031"},{"key":"16890_CR21","first-page":"386","volume":"9","author":"H Zamani","year":"2020","unstructured":"Zamani H, Nadimi-Shahraki MH, Taghian S, Banaie-Dezfouli M (2020) Enhancement of bernstain-search differential evolution algorithm to solve constrained engineering problems. Int J Comput Sci Eng 9:386\u2013396","journal-title":"Int J Comput Sci Eng"},{"key":"16890_CR22","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of ICNN\u201995-international conference on neural networks, Vol 4. IEEE, pp 1942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"1","key":"16890_CR23","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s00521-013-1367-1","volume":"24","author":"X-S Yang","year":"2014","unstructured":"Yang X-S, Deb S (2014) Cuckoo search: recent advances and applications. Neural Comput & Applic 24(1):169\u2013174","journal-title":"Neural Comput & Applic"},{"key":"16890_CR24","doi-asserted-by":"crossref","unstructured":"Hussien AG, Heidari AA, Ye X, Liang G, Chen H, Pan Z (2022) Boosting whale optimization with evolution strategy and gaussian random walks: an image segmentation method. Engineering with Computers 1\u201345","DOI":"10.1007\/s00366-021-01542-0"},{"issue":"4","key":"16890_CR25","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1007\/s10489-017-1019-8","volume":"48","author":"SZ Mirjalili","year":"2018","unstructured":"Mirjalili SZ, Mirjalili S, Saremi S, Faris H, Aljarah I (2018) Grasshopper optimization algorithm for multi-objective optimization problems. Appl Intell 48(4):805\u2013820","journal-title":"Appl Intell"},{"issue":"16","key":"16890_CR26","doi-asserted-by":"crossref","first-page":"6374","DOI":"10.1016\/j.eswa.2013.05.041","volume":"40","author":"E Cuevas","year":"2013","unstructured":"Cuevas E, Cienfuegos M, Zald\u00edvar D, P\u00e9rez-Cisneros M (2013) A swarm optimization algorithm inspired in the behavior of the social-spider. Expert Syst Appl 40(16):6374\u20136384","journal-title":"Expert Syst Appl"},{"key":"16890_CR27","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) The ant lion optimizer. Adv Eng Softw 83:80\u201398","journal-title":"Adv Eng Softw"},{"key":"16890_CR28","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.108320","volume":"242","author":"FA Hashim","year":"2022","unstructured":"Hashim FA, Hussien AG (2022) Snake optimizer: A novel meta-heuristic optimization algorithm. Knowl-Based Syst 242:108320","journal-title":"Knowl-Based Syst"},{"issue":"10","key":"16890_CR29","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.3390\/math10101696","volume":"10","author":"S Wang","year":"2022","unstructured":"Wang S, Hussien AG, Jia H, Abualigah L, Zheng R (2022) Enhanced remora optimization algorithm for solving constrained engineering optimization problems. Mathematics 10(10):1696","journal-title":"Mathematics"},{"issue":"8","key":"16890_CR30","doi-asserted-by":"crossref","first-page":"1311","DOI":"10.3390\/math10081311","volume":"10","author":"R Zheng","year":"2022","unstructured":"Zheng R, Hussien AG, Jia H-M, Abualigah L, Wang S, Wu D (2022) An improved wild horse optimizer for solving optimization problems. Mathematics 10(8):1311","journal-title":"Mathematics"},{"issue":"4","key":"16890_CR31","doi-asserted-by":"crossref","first-page":"2353","DOI":"10.1007\/s10489-020-01947-2","volume":"51","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Elaziz MA, Hussien AG, Alsalibi B, Jalali SMJ, Gandomi AH (2021) Lightning search algorithm: a comprehensive survey. Appl Intell 51(4):2353\u20132376","journal-title":"Appl Intell"},{"key":"16890_CR32","doi-asserted-by":"crossref","first-page":"173548","DOI":"10.1109\/ACCESS.2020.3024108","volume":"8","author":"AG Hussien","year":"2020","unstructured":"Hussien AG, Amin M, Wang M, Liang G, Alsanad A, Gumaei A, Chen H (2020) Crow search algorithm: theory, recent advances, and applications. IEEE Access 8:173548\u2013173565","journal-title":"IEEE Access"},{"key":"16890_CR33","doi-asserted-by":"crossref","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S, Abd Elaziz M, Gandomi AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609","journal-title":"Comput Methods Appl Mech Eng"},{"key":"16890_CR34","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2021.107250","volume":"157","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Yousri D, Abd Elaziz M, Ewees AA, Al-Qaness MA, Gandomi AH (2021) Aquila optimizer: a novel meta-heuristic optimization algorithm. Comput Ind Eng 157:107250","journal-title":"Comput Ind Eng"},{"issue":"4","key":"16890_CR35","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1080\/0952813X.2020.1737246","volume":"32","author":"AG Hussien","year":"2020","unstructured":"Hussien AG, Amin M, Abd El Aziz M (2020) A comprehensive review of moth-flame optimisation: variants, hybrids, and applications. J Exp Theor Artif Intell 32(4):705\u2013725","journal-title":"J Exp Theor Artif Intell"},{"key":"16890_CR36","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.116158","volume":"191","author":"L Abualigah","year":"2022","unstructured":"Abualigah L, Abd Elaziz M, Sumari P, Geem ZW, Gandomi AH (2022) Reptile search algorithm (rsa): A nature-inspired meta-heuristic optimizer. Expert Syst Appl 191:116158","journal-title":"Expert Syst Appl"},{"key":"16890_CR37","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Grey wolf optimizer. Adv Eng Softw"},{"issue":"1","key":"16890_CR38","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","volume":"267","author":"JH Holland","year":"1992","unstructured":"Holland JH (1992) Genetic algorithms. Sci Am 267(1):66\u201373","journal-title":"Sci Am"},{"issue":"1","key":"16890_CR39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/jsir.2010010101","volume":"1","author":"KM Passino","year":"2010","unstructured":"Passino KM (2010) Bacterial foraging optimization. Int J Swarm Intell Res (IJSIR) 1(1):1\u201316","journal-title":"Int J Swarm Intell Res (IJSIR)"},{"key":"16890_CR40","doi-asserted-by":"crossref","unstructured":"Price KV (2013) Differential evolution. In: Handbook of optimization, Springer, pp 187\u2013214","DOI":"10.1007\/978-3-642-30504-7_8"},{"key":"16890_CR41","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.asoc.2015.03.003","volume":"31","author":"SA Uymaz","year":"2015","unstructured":"Uymaz SA, Tezel G, Yel E (2015) Artificial algae algorithm (aaa) for nonlinear global optimization. Appl Soft Comput 31:153\u2013171","journal-title":"Appl Soft Comput"},{"issue":"6","key":"16890_CR42","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1109\/TEVC.2008.919004","volume":"12","author":"D Simon","year":"2008","unstructured":"Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702\u2013713","journal-title":"IEEE Trans Evol Comput"},{"issue":"4598","key":"16890_CR43","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1126\/science.220.4598.671","volume":"220","author":"S Kirkpatrick","year":"1983","unstructured":"Kirkpatrick S, Gelatt CD Jr, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671\u2013680","journal-title":"Science"},{"issue":"2","key":"16890_CR44","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.advengsoft.2005.04.005","volume":"37","author":"OK Erol","year":"2006","unstructured":"Erol OK, Eksin I (2006) A new optimization method: big bang-big crunch. Adv Eng Softw 37(2):106\u2013111","journal-title":"Adv Eng Softw"},{"key":"16890_CR45","doi-asserted-by":"crossref","unstructured":"Abualigah L, Elaziz MA, Sumari P, Khasawneh AM, Alshinwan M, Mirjalili S, Shehab M, Abuaddous HY, Gandomi AH (2022) Black hole algorithm: A comprehensive survey. Appl Intell 1\u201324","DOI":"10.1007\/s10489-021-02980-5"},{"issue":"13","key":"16890_CR46","doi-asserted-by":"crossref","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","volume":"179","author":"E Rashedi","year":"2009","unstructured":"Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) Gsa: a gravitational search algorithm. Inf Sci 179(13):2232\u20132248","journal-title":"Inf Sci"},{"issue":"2","key":"16890_CR47","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Mirjalili SM, Hatamlou A (2016) Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput & Applic 27(2):495\u2013513","journal-title":"Neural Comput & Applic"},{"key":"16890_CR48","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.future.2019.07.015","volume":"101","author":"FA Hashim","year":"2019","unstructured":"Hashim FA, Houssein EH, Mabrouk MS, Al-Atabany W, Mirjalili S (2019) Henry gas solubility optimization: A novel physics-based algorithm. Futur Gener Comput Syst 101:646\u2013667","journal-title":"Futur Gener Comput Syst"},{"key":"16890_CR49","doi-asserted-by":"crossref","DOI":"10.1016\/j.cma.2022.114570","volume":"391","author":"JO Agushaka","year":"2022","unstructured":"Agushaka JO, Ezugwu AE, Abualigah L (2022) Dwarf mongoose optimization algorithm. Comput Methods Appl Mech Eng 391:114570","journal-title":"Comput Methods Appl Mech Eng"},{"key":"16890_CR50","doi-asserted-by":"crossref","unstructured":"Ezugwu AE, Agushaka JO, Abualigah L, Mirjalili S, Gandomi AH (2022) Prairie dog optimization algorithm. Neural Comput & Applic 1\u201349","DOI":"10.1007\/s00521-022-07530-9"},{"issue":"5","key":"16890_CR51","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1515\/mt-2020-0076","volume":"63","author":"D G\u00fcrses","year":"2021","unstructured":"G\u00fcrses D, Bureerat S, Sait SM, Y\u0131ld\u0131z AR (2021) Comparison of the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, the salp swarm algorithm for real-world engineering applications. Mater Test 63(5):448\u2013452","journal-title":"Mater Test"},{"key":"16890_CR52","doi-asserted-by":"crossref","DOI":"10.1016\/j.compstruct.2021.114287","volume":"273","author":"S Khatir","year":"2021","unstructured":"Khatir S, Tiachacht S, Le Thanh C, Ghandourah E, Mirjalili S, Wahab MA (2021) An improved artificial neural network using arithmetic optimization algorithm for damage assessment in fgm composite plates. Compos Struct 273:114287","journal-title":"Compos Struct"},{"key":"16890_CR53","doi-asserted-by":"crossref","first-page":"84263","DOI":"10.1109\/ACCESS.2021.3085529","volume":"9","author":"M Premkumar","year":"2021","unstructured":"Premkumar M, Jangir P, Kumar BS, Sowmya R, Alhelou HH, Abualigah L, Yildiz AR, Mirjalili S (2021) A new arithmetic optimization algorithm for solving real-world multiobjective cec-2021 constrained optimization problems: diversity analysis and validations. IEEE Access 9:84263\u201384295","journal-title":"IEEE Access"},{"issue":"13","key":"16890_CR54","doi-asserted-by":"crossref","first-page":"2351","DOI":"10.3390\/math10132351","volume":"10","author":"I Al-Shourbaji","year":"2022","unstructured":"Al-Shourbaji I, Kachare PH, Alshathri S, Duraibi S, Elnaim B, Abd Elaziz M (2022) An efficient parallel reptile search algorithm and snake optimizer approach for feature selection. Mathematics 10(13):2351","journal-title":"Mathematics"},{"key":"16890_CR55","doi-asserted-by":"crossref","unstructured":"Deeb H, Sarangi A, Mishra D, Sarangi SK (2023) Improved black hole optimization algorithm for data clustering. Journal of King Saud University-Computer and Information Sciences","DOI":"10.1016\/j.jksuci.2020.12.013"},{"key":"16890_CR56","doi-asserted-by":"crossref","unstructured":"Fan Q, Chen Z, Li Z, Xia Z, Lin Y (2020) An efficient refracted salp swarm algorithm and its application in structural parameter identification. Engineering with Computers 1\u201315","DOI":"10.1007\/s00366-020-01034-7"},{"key":"16890_CR57","doi-asserted-by":"crossref","first-page":"160297","DOI":"10.1109\/ACCESS.2020.3013332","volume":"8","author":"X Zhang","year":"2020","unstructured":"Zhang X, Zhao K, Niu Y (2020) Improved harris hawks optimization based on adaptive cooperative foraging and dispersed foraging strategies. IEEE Access 8:160297\u2013160314","journal-title":"IEEE Access"},{"key":"16890_CR58","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2019.106018","volume":"89","author":"VK Kamboj","year":"2020","unstructured":"Kamboj VK, Nandi A, Bhadoria A, Sehgal S (2020) An intensify harris hawks optimizer for numerical and engineering optimization problems. Appl Soft Comput 89:106018","journal-title":"Appl Soft Comput"},{"key":"16890_CR59","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.eswa.2018.06.023","volume":"112","author":"AA Ewees","year":"2018","unstructured":"Ewees AA, Abd Elaziz M, Houssein EH (2018) Improved grasshopper optimization algorithm using opposition-based learning. Expert Syst Appl 112:156\u2013172","journal-title":"Expert Syst Appl"},{"issue":"15","key":"16890_CR60","doi-asserted-by":"crossref","first-page":"11195","DOI":"10.1007\/s00521-019-04629-4","volume":"32","author":"L Abualigah","year":"2020","unstructured":"Abualigah L, Shehab M, Alshinwan M, Alabool H (2020) Salp swarm algorithm: a comprehensive survey. Neural Comput & Applic 32(15):11195\u201311215","journal-title":"Neural Comput & Applic"},{"issue":"23","key":"16890_CR61","doi-asserted-by":"crossref","first-page":"2975","DOI":"10.3390\/electronics10232975","volume":"10","author":"MH Nadimi-Shahraki","year":"2021","unstructured":"Nadimi-Shahraki MH, Taghian S, Mirjalili S, Abualigah L, Abd Elaziz M, Oliva D (2021) Ewoa-opf: effective whale optimization algorithm to solve optimal power flow problem. Electronics 10(23):2975","journal-title":"Electronics"},{"issue":"4","key":"16890_CR62","doi-asserted-by":"crossref","first-page":"2567","DOI":"10.1007\/s10462-020-09909-3","volume":"54","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A (2021) Advances in sine cosine algorithm: a comprehensive survey. Artif Intell Rev 54(4):2567\u20132608","journal-title":"Artif Intell Rev"},{"issue":"2","key":"16890_CR63","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1007\/s11276-021-02866-x","volume":"28","author":"M Otair","year":"2022","unstructured":"Otair M, Ibrahim OT, Abualigah L, Altalhi M, Sumari P (2022) An enhanced grey wolf optimizer based particle swarm optimizer for intrusion detection system in wireless sensor networks. Wirel Netw 28(2):721\u2013744","journal-title":"Wirel Netw"},{"key":"16890_CR64","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1016\/j.jocs.2017.07.018","volume":"25","author":"LM Abualigah","year":"2018","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018) A new feature selection method to improve the document clustering using particle swarm optimization algorithm. J Comput Sci 25:456\u2013466","journal-title":"J Comput Sci"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-16890-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-16890-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-16890-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T06:58:05Z","timestamp":1709881085000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-16890-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,22]]},"references-count":64,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,3]]}},"alternative-id":["16890"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-16890-w","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,22]]},"assertion":[{"value":"21 September 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 June 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 September 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that there is no conflict of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}