{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T16:07:59Z","timestamp":1781021279109,"version":"3.54.1"},"reference-count":69,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.asoc.2026.115425","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T12:11:05Z","timestamp":1778760665000},"page":"115425","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Dynamic ensemble selection via optimization of competence regions"],"prefix":"10.1016","volume":"200","author":[{"given":"Behzad","family":"Abbasi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vahid","family":"Majidnezhad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bagher","family":"Zarei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saeid","family":"Taghavi Afshord","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.asoc.2026.115425_bib0005","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-019-0217-0","article-title":"Big data in healthcare: management, analysis and future prospects","volume":"6","author":"Dash","year":"2019","journal-title":"J. Big Data"},{"key":"10.1016\/j.asoc.2026.115425_bib0010","unstructured":"G. Mahajan, B. Saini, Educational data mining: a state-of-the-art survey on tools and techniques used in EDM, 2020, https:\/\/api.semanticscholar.org\/CorpusID:216123137"},{"key":"10.1016\/j.asoc.2026.115425_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.techfore.2021.120607","article-title":"Big data-enabled large-scale group decision making for circular economy: an emerging market context","volume":"166","author":"Modgil","year":"2021","journal-title":"Technol. Forecast. Soc. Change"},{"key":"10.1016\/j.asoc.2026.115425_bib0020","series-title":"Entertainment in Era of AI, Big Data & IoT","first-page":"87","author":"Hallur","year":"2021"},{"issue":"4","key":"10.1016\/j.asoc.2026.115425_bib0025","doi-asserted-by":"crossref","first-page":"222","DOI":"10.63180\/jcsra.thestap.2025.4.3","article-title":"A novel permissioned blockchain approach for scalable and privacy-preserving IoT authentication","volume":"2025","author":"Addula","year":"2025","journal-title":"J. Cyber Secur. Risk Audit."},{"key":"10.1016\/j.asoc.2026.115425_bib0030","article-title":"Few-shot fault diagnosis for machinery using multi-scale perception multi-level feature fusion image quadrant entropy","volume":"63","author":"Wang","year":"2025","journal-title":"Adv. Eng. Info."},{"key":"10.1016\/j.asoc.2026.115425_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2024.110745","article-title":"A generalized fault diagnosis framework for rotating machinery based on phase entropy","volume":"256","author":"Wang","year":"2025","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"10.1016\/j.asoc.2026.115425_bib0040","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.inffus.2017.09.010","article-title":"Dynamic classifier selection: recent advances and perspectives","volume":"41","author":"Cruz","year":"2018","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.asoc.2026.115425_bib0045","doi-asserted-by":"crossref","first-page":"32082","DOI":"10.1109\/ACCESS.2023.3262836","article-title":"An enhanced dynamic ensemble selection classifier for imbalance classification with application to China corporation bond default prediction","volume":"11","author":"Wang","year":"2023","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.asoc.2026.115425_bib0050","doi-asserted-by":"crossref","first-page":"1278","DOI":"10.1109\/TNNLS.2022.3183120","article-title":"Dynamic ensemble selection for imbalanced data streams with concept drift","volume":"35","author":"Jiao","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"11","key":"10.1016\/j.asoc.2026.115425_bib0055","doi-asserted-by":"crossref","first-page":"3665","DOI":"10.1016\/j.patcog.2014.05.003","article-title":"Dynamic selection of classifiers\u2014a comprehensive review","volume":"47","author":"Britto","year":"2014","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.asoc.2026.115425_bib0060","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.inffus.2020.09.004","article-title":"Preprocessed dynamic classifier ensemble selection for highly imbalanced drifted data streams","volume":"66","author":"Zyblewski","year":"2021","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.asoc.2026.115425_bib0065","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.neucom.2013.08.004","article-title":"LibD3C: ensemble classifiers with a clustering and dynamic selection strategy","volume":"123","author":"Lin","year":"2014","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2026.115425_bib0070","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1007\/978-3-642-04146-4_106","article-title":"On a new measure of classifier competence applied to the design of multiclassifier systems","volume":"5716","author":"Woloszynski","year":"2009","journal-title":"Lect. Notes Comput. Sci."},{"issue":"3","key":"10.1016\/j.asoc.2026.115425_bib0075","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.inffus.2011.03.007","article-title":"A measure of competence based on random classification for dynamic ensemble selection","volume":"13","author":"Woloszynski","year":"2012","journal-title":"Inf. Fusion"},{"issue":"10\u201311","key":"10.1016\/j.asoc.2026.115425_bib0080","doi-asserted-by":"crossref","first-page":"2656","DOI":"10.1016\/j.patcog.2011.03.020","article-title":"A probabilistic model of classifier competence for dynamic ensemble selection","volume":"44","author":"Woloszynski","year":"2011","journal-title":"Pattern Recognit."},{"issue":"3\u20134","key":"10.1016\/j.asoc.2026.115425_bib0085","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1007\/s00521-011-0737-9","article-title":"Dynamic selection approaches for multiple classifier systems","volume":"22","author":"Cavalin","year":"2013","journal-title":"Neural Comput. Appl."},{"issue":"5","key":"10.1016\/j.asoc.2026.115425_bib0090","doi-asserted-by":"crossref","first-page":"1925","DOI":"10.1016\/j.patcog.2014.12.003","article-title":"META-DES: a dynamic ensemble selection framework using meta-learning","volume":"48","author":"Cruz","year":"2015","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.asoc.2026.115425_bib0095","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.inffus.2017.02.010","article-title":"META-DES.Oracle: meta-learning and feature selection for dynamic ensemble selection","volume":"38","author":"Cruz","year":"2017","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.asoc.2026.115425_bib0100","series-title":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","first-page":"1164","article-title":"Learning classifier competence based on graph for dynamic classifier selection","author":"Hou","year":"2016"},{"issue":"9","key":"10.1016\/j.asoc.2026.115425_bib0105","doi-asserted-by":"crossref","first-page":"3188","DOI":"10.1007\/s10489-019-01435-2","article-title":"Graph-based dynamic ensemble pruning for facial expression recognition","volume":"49","author":"Li","year":"2019","journal-title":"Appl. Intell."},{"issue":"4","key":"10.1016\/j.asoc.2026.115425_bib0110","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1109\/34.588027","article-title":"Combination of multiple classifiers using local accuracy estimates","volume":"19","author":"Woods","year":"1997","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"10.1016\/j.asoc.2026.115425_bib0115","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1109\/TGRS.2002.1006354","article-title":"Multiple classifier systems for supervised remote sensing image classification based on dynamic classifier selection","volume":"40","author":"Smits","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.asoc.2026.115425_bib0120","series-title":"IEEE International Joint Conference on Neural Networks (IJCNN)","first-page":"1310","article-title":"Using accuracy and diversity to select classifiers to build ensembles","author":"Soares","year":"2006"},{"issue":"5","key":"10.1016\/j.asoc.2026.115425_bib0125","doi-asserted-by":"crossref","first-page":"1718","DOI":"10.1016\/j.patcog.2007.10.015","article-title":"From dynamic classifier selection to dynamic ensemble selection","volume":"41","author":"Ko","year":"2008","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.asoc.2026.115425_bib0130","series-title":"International Conference on Document Analysis and Recognition (ICDAR)","first-page":"163","article-title":"Classifier combination for hand-printed digit recognition","author":"Sabourin","year":"2002"},{"issue":"9","key":"10.1016\/j.asoc.2026.115425_bib0135","doi-asserted-by":"crossref","first-page":"1879","DOI":"10.1016\/S0031-3203(00)00150-3","article-title":"Dynamic classifier selection based on multiple classifier behaviour","volume":"34","author":"Giacinto","year":"2001","journal-title":"Pattern Recognit."},{"issue":"32","key":"10.1016\/j.asoc.2026.115425_bib0140","doi-asserted-by":"crossref","first-page":"20295","DOI":"10.1007\/s00521-024-10237-8","article-title":"Enhancing dynamic ensemble selection: combining self-generating prototypes and meta-classifier for data classification","volume":"36","author":"Manastarla","year":"2024","journal-title":"Neural Comput. Appl."},{"issue":"16","key":"10.1016\/j.asoc.2026.115425_bib0145","doi-asserted-by":"crossref","first-page":"12241","DOI":"10.1007\/s00500-020-04668-3","article-title":"Dynamic ensemble selection based on hesitant fuzzy multiple criteria decision making","volume":"24","author":"Elmi","year":"2020","journal-title":"Soft Comput."},{"key":"10.1016\/j.asoc.2026.115425_bib0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110899","article-title":"DES-AS: dynamic ensemble selection based on algorithm shapley","volume":"157","author":"Zhang","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.asoc.2026.115425_bib0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2021.107257","article-title":"Multi-layer selector (MLS): dynamic selection based on filtering some competence measures","volume":"104","author":"Elmi","year":"2021","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.asoc.2026.115425_bib0160","series-title":"International Joint Conference on Neural Networks (IJCNN)","first-page":"4396","article-title":"Contribution of data complexity features on dynamic classifier selection","author":"Brun","year":"2016"},{"key":"10.1016\/j.asoc.2026.115425_bib0165","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1007\/978-3-319-46128-1_26","article-title":"CHADE: metalearning with classifier chains for dynamic combination of classifiers","volume":"9851","author":"Pinto","year":"2016","journal-title":"Lect. Notes Comput. Sci."},{"key":"10.1016\/j.asoc.2026.115425_bib0170","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/978-3-319-71249-9_11","article-title":"Dynamic ensemble selection with probabilistic classifier chains","volume":"10534","author":"Narassiguin","year":"2017","journal-title":"Lect. Notes Comput. Sci."},{"key":"10.1016\/j.asoc.2026.115425_bib0175","series-title":"IEEE International Conference on Tools with Artificial Intelligence (ICTAI)","first-page":"765","article-title":"Dynamic ensemble selection by K-nearest local oracles with discrimination index","author":"Pereira","year":"2018"},{"key":"10.1016\/j.asoc.2026.115425_bib0180","doi-asserted-by":"crossref","first-page":"40743","DOI":"10.1109\/ACCESS.2021.3063254","article-title":"DDES: a distribution-based dynamic ensemble selection framework","volume":"9","author":"Choi","year":"2021","journal-title":"IEEE Access"},{"issue":"6","key":"10.1016\/j.asoc.2026.115425_bib0185","doi-asserted-by":"crossref","first-page":"2137","DOI":"10.1007\/s13042-022-01751-z","article-title":"A novel framework based on the multi-label classification for dynamic selection of classifiers","volume":"14","author":"Elmi","year":"2023","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"10.1016\/j.asoc.2026.115425_bib0190","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.inffus.2022.09.010","article-title":"OLP++: an online local classifier for high dimensional data","volume":"90","author":"Souza","year":"2023","journal-title":"Inf. Fusion"},{"issue":"1","key":"10.1016\/j.asoc.2026.115425_bib0195","first-page":"238","article-title":"Metaheuristic algorithms for optimization: a brief review","volume":"59","author":"Tomar","year":"2024","journal-title":"Eng. Proc."},{"issue":"3","key":"10.1016\/j.asoc.2026.115425_bib0200","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1007\/s12065-021-00590-1","article-title":"Chaotic vortex search algorithm: metaheuristic algorithm for feature selection","volume":"15","author":"Gharehchopogh","year":"2022","journal-title":"Evol. Intell."},{"issue":"6","key":"10.1016\/j.asoc.2026.115425_bib0205","doi-asserted-by":"crossref","first-page":"1896","DOI":"10.1109\/TEVC.2023.3238420","article-title":"SFE: a simple, fast, and efficient feature selection algorithm for high-dimensional data","volume":"27","author":"Ahadzadeh","year":"2023","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.115425_bib0210","series-title":"2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA)","article-title":"Machine learning-based orange quality classification: a hyperparameter optimization approach through puma optimizer","author":"Akbulut","year":"2025"},{"key":"10.1016\/j.asoc.2026.115425_bib0215","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2026.131088","article-title":"A modified starfish optimization algorithm (M-SFOA) for global optimization problems and its application to heart disease risk prediction","volume":"307","author":"Akbulut","year":"2026","journal-title":"Expert Syst. Appl."},{"issue":"13","key":"10.1016\/j.asoc.2026.115425_bib0220","doi-asserted-by":"crossref","first-page":"11025","DOI":"10.1007\/s00371-025-04084-4","article-title":"Meta-heuristic optimization for optimal block size in multi-focus image fusion: a comprehensive comparative study","volume":"41","author":"Akbulut","year":"2025","journal-title":"Vis. Comput."},{"key":"10.1016\/j.asoc.2026.115425_bib0225","first-page":"1","article-title":"Enhancing cryptocurrency price prediction through inter-coin volatility and hyperparameter optimization","author":"Hafidi","year":"2025","journal-title":"Comput. Econ."},{"issue":"5","key":"10.1016\/j.asoc.2026.115425_bib0230","doi-asserted-by":"crossref","first-page":"1947","DOI":"10.19139\/soic-2310-5070-2035","article-title":"Cryptocurrency price prediction with genetic algorithm-based hyperparameter optimization","volume":"13","author":"Hafidi","year":"2025","journal-title":"Stat., Optim. Inf. Comput."},{"issue":"13","key":"10.1016\/j.asoc.2026.115425_bib0235","doi-asserted-by":"crossref","first-page":"7471","DOI":"10.1007\/s00521-024-09472-w","article-title":"Hybrid particle swarm optimization algorithm for text feature selection problems","volume":"36","author":"Nachaoui","year":"2024","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.asoc.2026.115425_bib0240","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2021.116505","article-title":"A regularization by denoising super-resolution method based on genetic algorithms","volume":"99","author":"Nachaoui","year":"2021","journal-title":"Signal Process. Image Commun."},{"issue":"5","key":"10.1016\/j.asoc.2026.115425_bib0245","doi-asserted-by":"crossref","first-page":"1248","DOI":"10.1109\/TAI.2024.3521870","article-title":"Improved supervised machine learning for predicting auto insurance purchase patterns","volume":"6","author":"Nachaoui","year":"2025","journal-title":"IEEE Trans. Artif. Intell."},{"key":"10.1016\/j.asoc.2026.115425_bib0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.107567","article-title":"Primal dual algorithm for solving the nonsmooth twin SVM","volume":"128","author":"Lyaqini","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.asoc.2026.115425_bib0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.chaos.2021.111754","article-title":"An efficient primal-dual method for solving non-smooth machine learning problem","volume":"155","author":"Lyaqini","year":"2022","journal-title":"Chaos Solitons Fractals"},{"issue":"2","key":"10.1016\/j.asoc.2026.115425_bib0260","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.inffus.2008.11.003","article-title":"Overfitting cautious selection of classifier ensembles with genetic algorithms","volume":"10","author":"Santos","year":"2009","journal-title":"Inf. Fusion"},{"issue":"4","key":"10.1016\/j.asoc.2026.115425_bib0265","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.asoc.2005.11.001","article-title":"Genetic algorithms in classifier fusion","volume":"6","author":"Gabrys","year":"2006","journal-title":"Appl. Soft Comput."},{"issue":"1\u20132","key":"10.1016\/j.asoc.2026.115425_bib0270","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/S0004-3702(02)00190-X","article-title":"Ensembling neural networks: many could be better than all","volume":"137","author":"Zhou","year":"2002","journal-title":"Artif. Intell."},{"key":"10.1016\/j.asoc.2026.115425_bib0275","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.neucom.2013.01.052","article-title":"Optimal selection of ensemble classifiers using measures of competence and diversity of base classifiers","volume":"126","author":"Lysiak","year":"2014","journal-title":"Neurocomputing"},{"issue":"25","key":"10.1016\/j.asoc.2026.115425_bib0280","doi-asserted-by":"crossref","first-page":"15407","DOI":"10.1007\/s00521-024-09669-z","article-title":"ADE: advanced differential evolution","volume":"36","author":"Abbasi","year":"2024","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.asoc.2026.115425_bib0285","first-page":"3","article-title":"From theory to practice in particle swarm optimization","author":"Clerc","year":"2011","journal-title":"Particle Swarm Opt."},{"issue":"5","key":"10.1016\/j.asoc.2026.115425_bib0290","doi-asserted-by":"crossref","first-page":"710","DOI":"10.3390\/e25050710","article-title":"Recent developments in the theory and applicability of swarm search","volume":"25","author":"Altshuler","year":"2023","journal-title":"Entropy"},{"key":"10.1016\/j.asoc.2026.115425_bib0295","series-title":"Genetic algorithm - survey paper","author":"Thengade","year":"2012"},{"issue":"1","key":"10.1016\/j.asoc.2026.115425_bib0300","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/TEVC.2010.2059031","article-title":"Differential evolution: a survey of the state-of-the-art","volume":"15","author":"Das","year":"2011","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"10.1016\/j.asoc.2026.115425_bib0305","doi-asserted-by":"crossref","DOI":"10.1145\/2480741.2480752","article-title":"Exploration and exploitation in evolutionary algorithms","volume":"45","author":"Crepinsek","year":"2013","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.asoc.2026.115425_bib0310","series-title":"Teaching Learning Based Optimization Algorithm and Its Engineering Applications","author":"Rao","year":"2015"},{"key":"10.1016\/j.asoc.2026.115425_bib0315","doi-asserted-by":"crossref","DOI":"10.1016\/j.softx.2022.101262","article-title":"HS-Solver: spreadsheet based harmony search algorithm solver for various optimization problems","volume":"20","author":"Lee","year":"2022","journal-title":"Softwarex"},{"key":"10.1016\/j.asoc.2026.115425_bib0320","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1016\/j.future.2019.07.026","article-title":"An improved differential evolution algorithm using archimedean spiral and neighborhood search based mutation approach for cluster analysis","volume":"101","author":"Tarkhaneh","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"key":"10.1016\/j.asoc.2026.115425_bib0325","doi-asserted-by":"crossref","DOI":"10.1016\/j.apenergy.2025.125339","article-title":"Tribal intelligent evolution optimization and its application in optimal control of cooling plants","volume":"383","author":"Yao","year":"2025","journal-title":"Appl. Energy"},{"issue":"4","key":"10.1016\/j.asoc.2026.115425_bib0330","doi-asserted-by":"crossref","first-page":"104","DOI":"10.3390\/bdcc6040104","article-title":"An improved african vulture optimization algorithm for feature selection problems and its application of sentiment analysis on movie reviews","volume":"6","author":"Shaddeli","year":"2022","journal-title":"Big Data Cogn. Comput."},{"issue":"9\u201310","key":"10.1016\/j.asoc.2026.115425_bib0335","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1016\/S0262-8856(01)00045-2","article-title":"Design of effective neural network ensembles for image classification purposes","volume":"19","author":"Giacinto","year":"2001","journal-title":"Image Vis. Comput."},{"issue":"8","key":"10.1016\/j.asoc.2026.115425_bib0340","first-page":"1","article-title":"DESlib: a dynamic ensemble selection library in Python","volume":"21","author":"Cruz","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.asoc.2026.115425_bib0345","doi-asserted-by":"crossref","DOI":"10.1016\/j.sysarc.2023.102871","article-title":"MEALPY: an open-source library for latest meta-heuristic algorithms in Python","volume":"139","author":"Van Thieu","year":"2023","journal-title":"J. Syst. Archit."}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626008732?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626008732?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T15:56:13Z","timestamp":1781020573000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626008732"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":69,"alternative-id":["S1568494626008732"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115425","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dynamic ensemble selection via optimization of competence regions","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115425","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115425"}}