{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T17:52:31Z","timestamp":1774633951602,"version":"3.50.1"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T00:00:00Z","timestamp":1675814400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T00:00:00Z","timestamp":1675814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62176075"],"award-info":[{"award-number":["62176075"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2021MF063"],"award-info":[{"award-number":["ZR2021MF063"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1007\/s00521-023-08291-9","type":"journal-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T20:09:10Z","timestamp":1675886950000},"page":"11161-11182","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["An adaptive mutation strategy correction framework for differential evolution"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0124-0036","authenticated-orcid":false,"given":"Libao","family":"Deng","sequence":"first","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Yifan","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Chunlei","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Lili","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,8]]},"reference":[{"issue":"4","key":"8291_CR1","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J Glob Opt 11(4):341\u2013359","journal-title":"J Glob Opt"},{"key":"8291_CR2","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.ins.2019.08.040","volume":"507","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Gong D, Gao X, Tian T, Sun X (2020) Binary differential evolution with self-learning for multi-objective feature selection. Inform Sci 507:67\u201385","journal-title":"Inform Sci"},{"key":"8291_CR3","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107080","volume":"224","author":"W Deng","year":"2021","unstructured":"Deng W, Shang S, Cai X, Zhao H, Zhou Y, Chen H, Deng W (2021) Quantum differential evolution with cooperative coevolution framework and hybrid mutation strategy for large scale optimization. Knowl-Based Syst 224:107080","journal-title":"Knowl-Based Syst"},{"issue":"7","key":"8291_CR4","doi-asserted-by":"crossref","first-page":"2467","DOI":"10.1109\/TCYB.2018.2821180","volume":"49","author":"J Wang","year":"2018","unstructured":"Wang J, Weng T, Zhang Q (2018) A two-stage multiobjective evolutionary algorithm for multiobjective multidepot vehicle routing problem with time windows. IEEE Transact Cybernet 49(7):2467\u20132478","journal-title":"IEEE Transact Cybernet"},{"key":"8291_CR5","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.asoc.2018.03.033","volume":"68","author":"F Arce","year":"2018","unstructured":"Arce F, Zamora E, Sossa H, Barr\u00f3n R (2018) Differential evolution training algorithm for dendrite morphological neural networks. Appl Soft Comput 68:303\u2013313","journal-title":"Appl Soft Comput"},{"key":"8291_CR6","unstructured":"Ahmad MF, Isa NAM, Lim WH, Ang KM. Differential evolution: A recent review based on state-of-the-art works, Alex Eng J"},{"key":"8291_CR7","doi-asserted-by":"crossref","first-page":"68629","DOI":"10.1109\/ACCESS.2021.3077242","volume":"9","author":"AW Mohamed","year":"2021","unstructured":"Mohamed AW, Hadi AA, Mohamed AK (2021) Differential evolution mutations: Taxonomy, comparison and convergence analysis. IEEE Access 9:68629\u201368662","journal-title":"IEEE Access"},{"issue":"17","key":"8291_CR8","doi-asserted-by":"crossref","first-page":"5747","DOI":"10.1007\/s00500-017-2626-3","volume":"22","author":"G Sun","year":"2018","unstructured":"Sun G, Peng J, Zhao R (2018) Differential evolution with individual-dependent and dynamic parameter adjustment. Soft Comput 22(17):5747\u20135773","journal-title":"Soft Comput"},{"issue":"9","key":"8291_CR9","doi-asserted-by":"crossref","first-page":"6277","DOI":"10.1007\/s00500-019-03934-3","volume":"24","author":"G Sun","year":"2020","unstructured":"Sun G, Yang B, Yang Z, Xu G (2020) An adaptive differential evolution with combined strategy for global numerical optimization. Soft Comput 24(9):6277\u20136296","journal-title":"Soft Comput"},{"key":"8291_CR10","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.109280","volume":"251","author":"S Gupta","year":"2022","unstructured":"Gupta S, Su R (2022) An efficient differential evolution with fitness-based dynamic mutation strategy and control parameters. Knowl-Based Syst 251:109280","journal-title":"Knowl-Based Syst"},{"issue":"2","key":"8291_CR11","volume":"10","author":"H Hu","year":"2020","unstructured":"Hu H, Kantardzic M, Sethi TS (2020) No Free Lunch Theorem for concept drift detection in streaming data classification: A review. Wiley Interdisciplinary Rev: Data Mining Knowl Discov 10(2):e1327","journal-title":"Wiley Interdisciplinary Rev: Data Mining Knowl Discov"},{"issue":"1","key":"8291_CR12","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/s10489-016-0885-9","volume":"47","author":"X Li","year":"2017","unstructured":"Li X, Ma S, Hu J (2017) Multi-search differential evolution algorithm. Appl Intell 47(1):231\u2013256","journal-title":"Appl Intell"},{"key":"8291_CR13","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.ins.2018.01.014","volume":"435","author":"B Xu","year":"2018","unstructured":"Xu B, Chen X, Tao L (2018) Differential evolution with adaptive trial vector generation strategy and cluster-replacement-based feasibility rule for constrained optimization. Inform Sci 435:240\u2013262","journal-title":"Inform Sci"},{"key":"8291_CR14","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117669","volume":"206","author":"R Jiang","year":"2022","unstructured":"Jiang R, Shankaran R, Wang S, Chao T (2022) A proportional, integral and derivative differential evolution algorithm for global optimization. Expert Syst Appl 206:117669","journal-title":"Expert Syst Appl"},{"key":"8291_CR15","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.ins.2022.04.043","volume":"604","author":"Y Wang","year":"2022","unstructured":"Wang Y, Li T, Liu X, Yao J (2022) An adaptive clonal selection algorithm with multiple differential evolution strategies. Inform Sci 604:142\u2013169","journal-title":"Inform Sci"},{"issue":"3","key":"8291_CR16","doi-asserted-by":"crossref","first-page":"1571","DOI":"10.1007\/s12065-021-00568-z","volume":"15","author":"A Dixit","year":"2022","unstructured":"Dixit A, Mani A, Bansal R (2022) An adaptive mutation strategy for differential evolution algorithm based on particle swarm optimization. Evolutionary Intell 15(3):1571\u20131585","journal-title":"Evolutionary Intell"},{"key":"8291_CR17","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.ins.2020.11.023","volume":"549","author":"Z Tan","year":"2021","unstructured":"Tan Z, Li K, Wang Y (2021) Differential evolution with adaptive mutation strategy based on fitness landscape analysis. Inform Sci 549:142\u2013163","journal-title":"Inform Sci"},{"key":"8291_CR18","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2022.109419","volume":"127","author":"W Deng","year":"2022","unstructured":"Deng W, Ni H, Liu Y, Chen H, Zhao H (2022) An adaptive differential evolution algorithm based on belief space and generalized opposition-based learning for resource allocation. Appl Soft Comput 127:109419","journal-title":"Appl Soft Comput"},{"key":"8291_CR19","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.ins.2021.06.035","volume":"575","author":"L Deng","year":"2021","unstructured":"Deng L, Li C, Han R, Zhang L, Qiao L (2021) TPDE: A tri-population differential evolution based on zonal-constraint stepped division mechanism and multiple adaptive guided mutation strategies. Inform Sci 575:22\u201340","journal-title":"Inform Sci"},{"key":"8291_CR20","first-page":"2020","volume":"1\u20137","author":"PP Biswas","year":"2020","unstructured":"Biswas PP, Suganthan PN (2020) Large initial population and neighborhood search incorporated in lshade to solve cec2020 benchmark problems, in, IEEE Congress on Evolutionary Computation (CEC). IEEE 1\u20137:2020","journal-title":"IEEE"},{"issue":"4","key":"8291_CR21","doi-asserted-by":"crossref","first-page":"389","DOI":"10.3233\/IDT-180343","volume":"12","author":"SP Singh","year":"2018","unstructured":"Singh SP (2018) New adaption based mutation operator on differential evolution algorithm. Intell Decis Technol 12(4):389\u2013397","journal-title":"Intell Decis Technol"},{"key":"8291_CR22","doi-asserted-by":"crossref","unstructured":"Tanabe R, Fukunaga A (2013) Success-history based parameter adaptation for differential evolution, in, (2013) IEEE Congress on Evolutionary Computation. IEEE 71\u201378","DOI":"10.1109\/CEC.2013.6557555"},{"key":"8291_CR23","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.116298","volume":"192","author":"L Deng","year":"2022","unstructured":"Deng L, Li C, Lan Y, Sun G, Shang C (2022) Differential evolution with dynamic combination based mutation operator and two-level parameter adaptation strategy. Expert Syst Appl 192:116298","journal-title":"Expert Syst Appl"},{"issue":"5","key":"8291_CR24","doi-asserted-by":"crossref","first-page":"1615","DOI":"10.1007\/s00500-017-2885-z","volume":"23","author":"G Sun","year":"2019","unstructured":"Sun G, Lan Y, Zhao R (2019) Differential evolution with Gaussian mutation and dynamic parameter adjustment. Soft Comput 23(5):1615\u20131642","journal-title":"Soft Comput"},{"key":"8291_CR25","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.neucom.2021.01.003","volume":"435","author":"Y Xu","year":"2021","unstructured":"Xu Y, Yang X, Yang Z, Li X, Wang P, Ding R, Liu W (2021) An enhanced differential evolution algorithm with a new oppositional-mutual learning strategy. Neurocomputing 435:162\u2013175","journal-title":"Neurocomputing"},{"key":"8291_CR26","first-page":"2016","volume":"1\u20138","author":"KM Sallam","year":"2016","unstructured":"Sallam KM, Elsayed SM, Sarker RA (2016) Essam DL, Two-phase differential evolution framework for solving optimization problems, in, IEEE Symposium Series on Computational Intelligence (SSCI). IEEE 1\u20138:2016","journal-title":"IEEE"},{"key":"8291_CR27","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2019.07.037","volume":"138","author":"O Tarkhaneh","year":"2019","unstructured":"Tarkhaneh O, Shen H (2019) An adaptive differential evolution algorithm to optimal multi-level thresholding for MRI brain image segmentation. Expert Syst Appl 138:112820","journal-title":"Expert Syst Appl"},{"issue":"1","key":"8291_CR28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-37186-2","volume":"9","author":"J Wang","year":"2019","unstructured":"Wang J, Li S (2019) An improved grey wolf optimizer based on differential evolution and elimination mechanism. Sci Rep 9(1):1\u201321","journal-title":"Sci Rep"},{"key":"8291_CR29","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2019.112949","volume":"141","author":"G Yildizdan","year":"2020","unstructured":"Yildizdan G, Baykan \u00d6K (2020) A novel modified bat algorithm hybridizing by differential evolution algorithm. Expert Syst Appl 141:112949","journal-title":"Expert Syst Appl"},{"issue":"6","key":"8291_CR30","doi-asserted-by":"crossref","first-page":"3954","DOI":"10.1109\/TSMC.2019.2956121","volume":"51","author":"S Gao","year":"2019","unstructured":"Gao S, Yu Y, Wang Y, Wang J, Cheng J, Zhou M (2019) Chaotic local search-based differential evolution algorithms for optimization. IEEE Transact Syst Man Cybernet: Syst 51(6):3954\u20133967","journal-title":"IEEE Transact Syst Man Cybernet: Syst"},{"issue":"15","key":"8291_CR31","doi-asserted-by":"crossref","first-page":"9503","DOI":"10.1007\/s00521-021-05708-1","volume":"33","author":"G Sun","year":"2021","unstructured":"Sun G, Li C, Deng L (2021) An adaptive regeneration framework based on search space adjustment for differential evolution. Neural Comput Appl 33(15):9503\u20139519","journal-title":"Neural Comput Appl"},{"issue":"10","key":"8291_CR32","doi-asserted-by":"crossref","first-page":"3215","DOI":"10.1007\/s00500-017-2777-2","volume":"22","author":"AW Mohamed","year":"2018","unstructured":"Mohamed AW, Suganthan PN (2018) Real-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation. Soft Comput 22(10):3215\u20133235","journal-title":"Soft Comput"},{"issue":"2","key":"8291_CR33","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1007\/s13042-017-0711-7","volume":"10","author":"AW Mohamed","year":"2019","unstructured":"Mohamed AW, Mohamed AK (2019) Adaptive guided differential evolution algorithm with novel mutation for numerical optimization. Inter J Mach Learn Cybernet 10(2):253\u2013277","journal-title":"Inter J Mach Learn Cybernet"},{"key":"8291_CR34","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2019.105008","volume":"188","author":"M Tian","year":"2020","unstructured":"Tian M, Gao X, Yan X (2020) Performance-driven adaptive differential evolution with neighborhood topology for numerical optimization. Knowl-Based Syst 188:105008","journal-title":"Knowl-Based Syst"},{"key":"8291_CR35","volume":"241","author":"X Yan","year":"2022","unstructured":"Yan X, Tian M (2022) Differential evolution with two-level adaptive mechanism for numerical optimization. Knowl-Based Syst 241:108209","journal-title":"Knowl-Based Syst"},{"key":"8291_CR36","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2020.100816","volume":"61","author":"J Cheng","year":"2021","unstructured":"Cheng J, Pan Z, Liang H, Gao Z, Gao J (2021) Differential evolution algorithm with fitness and diversity ranking-based mutation operator. Swarm Evolutionary Comput 61:100816","journal-title":"Swarm Evolutionary Comput"},{"key":"8291_CR37","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1016\/j.ins.2022.07.043","volume":"608","author":"Z Cao","year":"2022","unstructured":"Cao Z, Wang Z, Fu Y, Jia H, Tian F (2022) An adaptive differential evolution framework based on population feature information. Inform Sci 608:1416\u20131440","journal-title":"Inform Sci"},{"key":"8291_CR38","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2022.101057","volume":"71","author":"A Ghosh","year":"2022","unstructured":"Ghosh A, Das S, Das AK, Senkerik R, Viktorin A, Zelinka I, Masegosa AD (2022) Using spatial neighborhoods for parameter adaptation: An improved success history based differential evolution. Swarm Evolutionary Comput 71:101057","journal-title":"Swarm Evolutionary Comput"},{"key":"8291_CR39","unstructured":"Li Y, Wang S, Yang B, Chen H, Wu Z, Yang H (2022) Population reduction with individual similarity for differential evolution, Artifi Intell Rev. 1\u201363"},{"key":"8291_CR40","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107150","volume":"226","author":"Z Zeng","year":"2021","unstructured":"Zeng Z, Zhang M, Chen T, Hong Z (2021) A new selection operator for differential evolution algorithm. Knowl-Based Syst 226:107150","journal-title":"Knowl-Based Syst"},{"key":"8291_CR41","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.ins.2022.07.075","volume":"609","author":"Z Zeng","year":"2022","unstructured":"Zeng Z, Hong Z, Zhang H, Zhang M, Chen C (2022) Improving differential evolution using a best discarded vector selection strategy. Inform Sci 609:353\u2013375","journal-title":"Inform Sci"},{"issue":"5","key":"8291_CR42","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1109\/TEVC.2009.2014613","volume":"13","author":"J Zhang","year":"2009","unstructured":"Zhang J, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Transact Evolutionary Comput 13(5):945\u2013958","journal-title":"IEEE Transact Evolutionary Comput"},{"key":"8291_CR43","unstructured":"Liang JJ, Qu BY, Suganthan PN (2013) Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective real-parameter numerical optimization. Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore 635:490"},{"key":"8291_CR44","unstructured":"Wu G, Mallipeddi R, Suganthan PN (2017) Problem definitions and evaluation criteria for the CEC 2017 competition on constrained real-parameter optimization, National University of Defense Technology, Changsha, Hunan, PR China and Kyungpook National University, Daegu, South Korea and Nanyang Technological University, Singapore, Technical Report"},{"key":"8291_CR45","unstructured":"Das S, Suganthan PN (2011) Problem definitions and evaluation criteria for CEC, competition on testing evolutionary algorithms on real world optimization problems. Jadavpur University, Nanyang Technological University, Kolkata 2010:341\u2013359"},{"issue":"3","key":"8291_CR46","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1016\/j.ejor.2006.06.043","volume":"185","author":"C Garc\u00eda-Mart\u00ednez","year":"2008","unstructured":"Garc\u00eda-Mart\u00ednez C, Lozano M, Herrera F, Molina D, S\u00e1nchez AM (2008) Global and local real-coded genetic algorithms based on parent-centric crossover operators. Eur J Operat Res 185(3):1088\u20131113","journal-title":"Eur J Operat Res"},{"issue":"1","key":"8291_CR47","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/4235.843494","volume":"4","author":"F Herrera","year":"2000","unstructured":"Herrera F, Lozano M (2000) Gradual distributed real-coded genetic algorithms. IEEE Transact Evolutionary Comput 4(1):43\u201363","journal-title":"IEEE Transact Evolutionary Comput"},{"key":"8291_CR48","first-page":"2014","volume":"1658\u20131665","author":"R Tanabe","year":"2014","unstructured":"Tanabe R, Fukunaga AS (2014) Improving the search performance of SHADE using linear population size reduction, in, IEEE congress on evolutionary computation (CEC). IEEE 1658\u20131665:2014","journal-title":"IEEE"},{"key":"8291_CR49","first-page":"2017","volume":"372\u2013379","author":"NH Awad","year":"2017","unstructured":"Awad NH, Ali MZ, Suganthan PN (2017) Ensemble sinusoidal differential covariance matrix adaptation with Euclidean neighborhood for solving CEC2017 benchmark problems, in, IEEE Congress on Evolutionary Computation (CEC). IEEE 372\u2013379:2017","journal-title":"IEEE"},{"issue":"1","key":"8291_CR50","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/s00500-020-05425-2","volume":"25","author":"X Zhao","year":"2021","unstructured":"Zhao X, Feng S, Hao J, Zuo X, Zhang Y (2021) Neighborhood opposition-based differential evolution with Gaussian perturbation. Soft Comput 25(1):27\u201346","journal-title":"Soft Comput"},{"issue":"5","key":"8291_CR51","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1109\/TEVC.2014.2375933","volume":"19","author":"S-M Guo","year":"2015","unstructured":"Guo S-M, Yang C-C, Hsu P-H, Tsai JS-H (2015) Improving differential evolution with a successful-parent-selecting framework. IEEE Transact Evolutionary Comput 19(5):717\u2013730","journal-title":"IEEE Transact Evolutionary Comput"},{"key":"8291_CR52","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.ins.2020.05.108","volume":"539","author":"L Deng","year":"2020","unstructured":"Deng L, Zhang L, Fu N, Sun H, Qiao L (2020) ERG-DE: An elites regeneration framework for differential evolution. Inform Sci 539:81\u2013103","journal-title":"Inform Sci"},{"key":"8291_CR53","doi-asserted-by":"crossref","unstructured":"Corder GW, Foreman DI (2009) Nonparametric Statistics for Non-Statisticians, John Wiley & Sons","DOI":"10.1002\/9781118165881"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08291-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08291-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08291-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,25]],"date-time":"2023-04-25T00:25:26Z","timestamp":1682382326000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08291-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,8]]},"references-count":53,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["8291"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08291-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,8]]},"assertion":[{"value":"21 June 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 January 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 February 2023","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"}}]}}