{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:50:13Z","timestamp":1761745813262},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"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":["Evolving Systems"],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s12530-023-09500-5","type":"journal-article","created":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T10:01:31Z","timestamp":1687082491000},"page":"829-848","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["AO-SAKEL: arithmetic optimization-based self-adaptive kernel extreme learning for international trade prediction"],"prefix":"10.1007","volume":"15","author":[{"given":"Vaishali","family":"Gupta","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ela","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,18]]},"reference":[{"key":"9500_CR1","doi-asserted-by":"publisher","unstructured":"Abualigah L, Diabat A, Mirjalili S, Abd Elaziz M, Gandomi AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376: 113609. https:\/\/doi.org\/10.1016\/j.cma.2020.113609","DOI":"10.1016\/j.cma.2020.113609"},{"key":"9500_CR2","doi-asserted-by":"publisher","first-page":"64929","DOI":"10.1109\/ACCESS.2021.3073507","volume":"9","author":"SS Alotaibi","year":"2021","unstructured":"Alotaibi SS (2021) Ensemble technique with optimal feature selection for Saudi stock market prediction: a novel hybrid red deer-grey algorithm. IEEE Access 9:64929\u201364944. https:\/\/doi.org\/10.1109\/ACCESS.2021.3073507","journal-title":"IEEE Access"},{"issue":"1","key":"9500_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cam.2004.06.004","volume":"175","author":"ZA Anastassi","year":"2005","unstructured":"Anastassi ZA, Simos TE (2005) An optimized Runge-Kutta method for the solution of orbital problems. J Comput Appl Math 175(1):1\u20139. https:\/\/doi.org\/10.1016\/j.cam.2004.06.004","journal-title":"J Comput Appl Math"},{"issue":"20","key":"9500_CR4","doi-asserted-by":"publisher","first-page":"7046","DOI":"10.1016\/j.eswa.2015.05.013","volume":"42","author":"M Ballings","year":"2015","unstructured":"Ballings M, Van den Poel D, Hespeels N, Gryp R (2015) Evaluating multiple classifiers for stock price direction prediction. Expert Syst Appl 42(20):7046\u20137056. https:\/\/doi.org\/10.1016\/j.eswa.2015.05.013","journal-title":"Expert Syst Appl"},{"key":"9500_CR5","doi-asserted-by":"publisher","unstructured":"Batarseh F, Gopinath M, Nalluru G, Beckman J (2019) Application of machine learning in forecasting international trade trends.\u00a0arXiv preprint arXiv:1910.03112. https:\/\/doi.org\/10.48550\/arXiv.1910.03112","DOI":"10.48550\/arXiv.1910.03112"},{"key":"9500_CR6","doi-asserted-by":"publisher","unstructured":"Batarseh FA, Gopinath M, Monken A, Gu Z (2021) Public policymaking for international agricultural trade using association rules and ensemble machine learning. Mach Learn Appl 5:100046. https:\/\/doi.org\/10.1016\/j.mlwa.2021.100046","DOI":"10.1016\/j.mlwa.2021.100046"},{"key":"9500_CR7","doi-asserted-by":"crossref","unstructured":"Chatterjee S, Sarkar S, Dey N, Ashour AS, Sen S (2018) Hybrid non-dominated sorting genetic algorithm: II-neural network approach. In: Adv Appl Metaheuristic Comput (pp. 264\u2013286) IGI Global.","DOI":"10.4018\/978-1-5225-4151-6.ch011"},{"key":"9500_CR8","doi-asserted-by":"publisher","unstructured":"Chen J, Luo C, Pan L, Jia Y (2021) Trading strategy of structured mutual fund based on deep learning network. Expert Syst Appl 183:115390. https:\/\/doi.org\/10.1016\/j.eswa.2021.115390","DOI":"10.1016\/j.eswa.2021.115390"},{"key":"9500_CR9","first-page":"1","volume":"1","author":"X Dong","year":"2021","unstructured":"Dong X (2021) Chen X (2021) Forecasting algorithm of tourism service trade based on PSO-optimized hybrid RVM model. EURASIP J Adv Signal Process 1:1\u201316","journal-title":"EURASIP J Adv Signal Process"},{"key":"9500_CR10","doi-asserted-by":"publisher","unstructured":"Essandoh OK, Islam M, Kakinaka M (2020) Linking international trade and foreign direct investment to CO2 emissions: any differences between developed and developing countries?. Sci Total Environ 712:136437. https:\/\/doi.org\/10.1016\/j.scitotenv.2019.136437","DOI":"10.1016\/j.scitotenv.2019.136437"},{"issue":"6","key":"9500_CR11","doi-asserted-by":"publisher","first-page":"1072","DOI":"10.3390\/pr10061072","volume":"10","author":"AY Hassan","year":"2022","unstructured":"Hassan AY, Ismaeel AA, Said M, Ghoniem RM, Deb S, Elsayed AG (2022) Evaluation of weighted mean of vectors algorithm for identification of solar cell parameters. Processes 10(6):1072","journal-title":"Processes"},{"key":"9500_CR12","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Futur Gener Comput Syst 97:849\u2013872","journal-title":"Futur Gener Comput Syst"},{"key":"9500_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.resconrec.2021.105591","volume":"170","author":"X Hu","year":"2021","unstructured":"Hu X, Wang C, Zhu X, Yao C, Ghadimi P (2021) Trade structure and risk transmission in the international automotive Li-ion batteries trade. Resour Conserv Recycl 170:105591","journal-title":"Resour Conserv Recycl"},{"key":"9500_CR14","doi-asserted-by":"publisher","unstructured":"Huynh HD, Dang LM, Duong D (2017) A new model for stock price movements prediction using deep neural network. In: Proceedings of the Eighth International Symposium on Information and Communication Technology (pp. 57\u201362). https:\/\/doi.org\/10.1145\/3155133.3155202","DOI":"10.1145\/3155133.3155202"},{"key":"9500_CR15","doi-asserted-by":"publisher","first-page":"140383","DOI":"10.1109\/ACCESS.2021.3119041","volume":"9","author":"SY Kuo","year":"2021","unstructured":"Kuo SY, Chou YH (2021) Building intelligent moving average-based stock trading system using metaheuristic algorithms. IEEE Access 9:140383\u2013140396","journal-title":"IEEE Access"},{"key":"9500_CR200","doi-asserted-by":"crossref","unstructured":"Joshi S, Andersen R, Jespersen B, Rittig S, (2013) Genetics of steroid\u2010resistant nephrotic syndrome: a review of mutation spectrum and suggested approach for genetic testing. Acta Paediatr 102(9):844\u2013856","DOI":"10.1111\/apa.12317"},{"key":"9500_CR16","doi-asserted-by":"publisher","first-page":"106824","DOI":"10.1109\/ACCESS.2021.3100359","volume":"9","author":"T Leangarun","year":"2021","unstructured":"Leangarun T, Tangamchit P, Thajchayapong S (2021) Stock price manipulation detection using deep unsupervised learning: the case of Thailand. IEEE Access 9:106824\u2013106838","journal-title":"IEEE Access"},{"key":"9500_CR17","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M, Heidari AA, Mirjalili S (2020) Slime mould algorithm: a new method for stochastic optimization. Futur Gener Comput Syst 111:300\u2013323. https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Futur Gener Comput Syst"},{"issue":"6","key":"9500_CR18","doi-asserted-by":"publisher","first-page":"1357","DOI":"10.1109\/TCSS.2021.3084847","volume":"8","author":"Y Li","year":"2021","unstructured":"Li Y, Wang S, Wei Y, Zhu Q (2021) A new hybrid VMD-ICSS-BiGRU approach for gold futures price forecasting and algorithmic trading. IEEE Transactions on Computational Social Systems 8(6):1357\u20131368","journal-title":"IEEE Transactions on Computational Social Systems"},{"issue":"6","key":"9500_CR19","doi-asserted-by":"publisher","first-page":"1342","DOI":"10.1080\/00207721.2014.924602","volume":"47","author":"C Ma","year":"2016","unstructured":"Ma C, Ouyang J, Chen HL, Ji JC (2016) A novel kernel extreme learning machine algorithm based on self-adaptive artificial bee colony optimisation strategy. Int J Syst Sci 47(6):1342\u20131357","journal-title":"Int J Syst Sci"},{"key":"9500_CR20","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1016\/j.neucom.2021.04.005","volume":"449","author":"C Ma","year":"2021","unstructured":"Ma C, Zhang J, Liu J, Ji L, Gao F (2021) A parallel multi-module deep reinforcement learning algorithm for stock trading. Neurocomputing 449:290\u2013302","journal-title":"Neurocomputing"},{"issue":"1","key":"9500_CR21","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1257\/089533003321164958","volume":"17","author":"BG Malkiel","year":"2003","unstructured":"Malkiel BG (2003) The efficient market hypothesis and its critics. Journal of Economic Perspectives 17(1):59\u201382","journal-title":"Journal of Economic Perspectives"},{"key":"9500_CR22","doi-asserted-by":"publisher","first-page":"86230","DOI":"10.1109\/ACCESS.2021.3088999","volume":"9","author":"N Naik","year":"2021","unstructured":"Naik N, Mohan BR (2021) Novel stock crisis prediction technique\u2014a study on indian stock market. IEEE Access 9:86230\u201386242","journal-title":"IEEE Access"},{"issue":"1","key":"9500_CR23","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/j.eswa.2014.07.040","volume":"42","author":"J Patel","year":"2015","unstructured":"Patel J, Shah S, Thakkar P, Kotecha K (2015) Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert Syst Appl 42(1):259\u2013268","journal-title":"Expert Syst Appl"},{"key":"9500_CR24","doi-asserted-by":"publisher","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. https:\/\/doi.org\/10.1109\/ACCESS.2021.3085529","journal-title":"IEEE Access"},{"key":"9500_CR25","doi-asserted-by":"publisher","unstructured":"Razmjooy N, Razmjooy S, Vahedi Z, Estrela VV, Oliveira, GGD (2021) A new design for robust control of power system stabilizer based on Moth search algorithm. In: Metaheuristics and Optimization in Computer and Electrical Engineering\u00a0(pp. 187\u2013202). Springer, Cham. https:\/\/link.springer.com\/chapter\/https:\/\/doi.org\/10.1007\/978-3-030-56689-0_10","DOI":"10.1007\/978-3-030-56689-0_10"},{"key":"9500_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.resourpol.2020.101591","volume":"66","author":"T Redmond","year":"2020","unstructured":"Redmond T, Nasir MA (2020) Role of natural resource abundance, international trade and financial development in the economic development of selected countries. Resour Policy 66:101591","journal-title":"Resour Policy"},{"key":"9500_CR27","doi-asserted-by":"publisher","first-page":"88981","DOI":"10.1109\/ACCESS.2021.3090834","volume":"9","author":"S Saha","year":"2021","unstructured":"Saha S, Gao J, Gerlach R (2021) Stock ranking prediction using list-wise approach and node embedding technique. IEEE Access 9:88981\u201388996","journal-title":"IEEE Access"},{"key":"9500_CR28","doi-asserted-by":"publisher","unstructured":"Shen ML, Lee CF, Liu HH, Chang PY,Yang CH (2021) Effective multinational trade forecasting using LSTM recurrent neural network.\u00a0Expert Systems with Applications\u00a0182:115199. https:\/\/doi.org\/10.1016\/j.eswa.2021.115199","DOI":"10.1016\/j.eswa.2021.115199"},{"key":"9500_CR29","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.physa.2016.08.031","volume":"465","author":"S Sokolov-Mladenovi\u0107","year":"2017","unstructured":"Sokolov-Mladenovi\u0107 S, Milovan\u010devi\u0107 M, Mladenovi\u0107 I (2017) Evaluation of trade influence on economic growth rate by computational intelligence approach. Physica A 465:358\u2013362. https:\/\/doi.org\/10.1016\/j.physa.2016.08.031","journal-title":"Physica A"},{"issue":"5","key":"9500_CR30","doi-asserted-by":"publisher","first-page":"3432","DOI":"10.48084\/etasr.2311","volume":"8","author":"J Sun","year":"2018","unstructured":"Sun J, Suo Y, Park S, Xu T, Liu Y, Wang W (2018) Analysis of bilateral trade flow and machine learning algorithms for GDP forecasting. Eng Technol Appl Sci Res 8(5):3432\u20133438","journal-title":"Eng Technol Appl Sci Res"},{"key":"9500_CR31","unstructured":"TiSMoS\u2014a new global trade in Services Data Set. (n.d.). Retrieved August 22, 2022, \/\/www.wto.org\/english\/tratop_e\/serv_e\/simply_services_29nov_2019_timos_presentation_e.pdf"},{"issue":"3","key":"9500_CR32","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1007\/s42235-021-0050-y","volume":"18","author":"J Tu","year":"2021","unstructured":"Tu J, Chen H, Wang M, Gandomi AH (2021) The colony predation algorithm. J Bionic Eng 18(3):674\u2013710","journal-title":"J Bionic Eng"},{"key":"9500_CR33","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.asoc.2016.07.024","volume":"49","author":"J Wang","year":"2016","unstructured":"Wang J, Hou R, Wang C, Shen L (2016) Improved v-support vector regression model based on variable selection and brainstorm optimization for stock price forecasting. Appl Soft Comput 49:164\u2013178","journal-title":"Appl Soft Comput"},{"issue":"7","key":"9500_CR34","doi-asserted-by":"publisher","first-page":"1995","DOI":"10.1007\/s00521-015-1923-y","volume":"31","author":"GG Wang","year":"2019","unstructured":"Wang GG, Deb S, Cui Z (2019) Monarch butterfly optimization. Neural Comput Appl 31(7):1995\u20132014","journal-title":"Neural Comput Appl"},{"key":"9500_CR35","unstructured":"World Trade Organization. WTO. (n.d.). Retrieved August 22, 2022, from https:\/\/www.wto.org\/english\/res_e\/statis_e\/trade_datasets_e.htm"},{"key":"9500_CR36","doi-asserted-by":"publisher","unstructured":"Xiao L, Shao W, Jin F, Wu Z (2021) A self-adaptive kernel extreme learning machine for short-term wind speed forecasting. Appl Soft Comput 99:106917. https:\/\/doi.org\/10.1016\/j.asoc.2020.106917","DOI":"10.1016\/j.asoc.2020.106917"},{"key":"9500_CR37","doi-asserted-by":"publisher","unstructured":"Yang Y, Chen H, Heidari AA, Gandomi AH (2021) Hunger games search: visions, conception, implementation, deep analysis, perspectives, and towards performance shifts. Expert Systems with Appl 177:114864. https:\/\/doi.org\/10.1016\/j.eswa.2021.114864","DOI":"10.1016\/j.eswa.2021.114864"},{"key":"9500_CR38","doi-asserted-by":"publisher","first-page":"22672","DOI":"10.1109\/ACCESS.2020.2969293","volume":"8","author":"X Yuan","year":"2020","unstructured":"Yuan X, Yuan J, Jiang T, Ain QU (2020) Integrated long-term stock selection models based on feature selection and machine learning algorithms for China stock market. IEEE Access 8:22672\u201322685","journal-title":"IEEE Access"},{"key":"9500_CR39","doi-asserted-by":"publisher","unstructured":"Zhai J, Cao Y, Ding X (2018) Data analytic approach for manipulation detection in stock market.\u00a0Review of Quantitative Finance and Accounting\u00a050(3):897\u2013932. https:\/\/link.springer.com\/article\/https:\/\/doi.org\/10.1007\/s11156-017-0650-0","DOI":"10.1007\/s11156-017-0650-0"}],"container-title":["Evolving Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-023-09500-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12530-023-09500-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-023-09500-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,4]],"date-time":"2024-06-04T11:20:24Z","timestamp":1717500024000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12530-023-09500-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,18]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["9500"],"URL":"https:\/\/doi.org\/10.1007\/s12530-023-09500-5","relation":{},"ISSN":["1868-6478","1868-6486"],"issn-type":[{"value":"1868-6478","type":"print"},{"value":"1868-6486","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,18]]},"assertion":[{"value":"23 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 March 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 June 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"}},{"value":"This article does not contain any studies with human participants.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"This article does not contain any studies with human or animal subjects performed by any of the authors.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal rights"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Not applicable.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}