{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T03:15:06Z","timestamp":1772334906722,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T00:00:00Z","timestamp":1731715200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T00:00:00Z","timestamp":1731715200000},"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":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s12652-024-04894-9","type":"journal-article","created":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T05:16:25Z","timestamp":1731734185000},"page":"189-205","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A hybrid model for assessing the price behavior of financial markets: a case study of the HSI"],"prefix":"10.1007","volume":"16","author":[{"given":"Xin","family":"Meng","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,16]]},"reference":[{"issue":"4","key":"4894_CR1","doi-asserted-by":"publisher","first-page":"101940","DOI":"10.1016\/j.jksus.2022.101940","volume":"34","author":"MM Akhtar","year":"2022","unstructured":"Akhtar MM, Zamani AS, Khan S, Shatat ASA, Dilshad S, Samdani F (2022) Stock market prediction based on statistical data using machine learning algorithms. J King Saud Univ - Sci 34(4):101940. https:\/\/doi.org\/10.1016\/j.jksus.2022.101940","journal-title":"J King Saud Univ - Sci"},{"key":"4894_CR4","doi-asserted-by":"publisher","first-page":"117949","DOI":"10.1016\/j.eswa.2022.117949","volume":"207","author":"A Ala","year":"2022","unstructured":"Ala A, Simic V, Pamucar D, Tirkolaee EB (2022) Appointment Scheduling Problem under Fairness Policy in Healthcare services: fuzzy ant Lion Optimizer. Expert Syst Appl 207:117949. https:\/\/doi.org\/10.1016\/j.eswa.2022.117949","journal-title":"Expert Syst Appl"},{"key":"4894_CR2","doi-asserted-by":"publisher","first-page":"111012","DOI":"10.1016\/j.asoc.2023.111012","volume":"150","author":"A Ala","year":"2024","unstructured":"Ala A, Goli A, Mirjalili S, Simic V (2024a) A fuzzy multi-objective optimization model for sustainable healthcare supply chain network design. Appl Soft Comput 150:111012. https:\/\/doi.org\/10.1016\/j.asoc.2023.111012","journal-title":"Appl Soft Comput"},{"key":"4894_CR3","doi-asserted-by":"publisher","first-page":"107889","DOI":"10.1016\/j.engappai.2024.107889","volume":"131","author":"A Ala","year":"2024","unstructured":"Ala A, Simic V, Pamucar D, Bacanin N (2024b) Enhancing patient information performance in internet of things-based smart healthcare system: hybrid artificial intelligence and optimization approaches. Eng Appl Artif Intell 131:107889. https:\/\/doi.org\/10.1016\/j.engappai.2024.107889","journal-title":"Eng Appl Artif Intell"},{"key":"4894_CR5","doi-asserted-by":"publisher","unstructured":"Ashfaq N, Nawaz Z, Ilyas M (2021) A comparative study of different machine learning regressors for Stock Market Prediction. https:\/\/doi.org\/10.48550\/arxiv.2104.07469","DOI":"10.48550\/arxiv.2104.07469"},{"issue":"2022","key":"4894_CR6","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/j.procs.2022.12.028","volume":"215","author":"M Bansal","year":"2022","unstructured":"Bansal M, Goyal A, Choudhary A (2022) Stock Market Prediction with High Accuracy using machine learning techniques. Procedia Comput Sci 215(2022):247\u2013265. https:\/\/doi.org\/10.1016\/j.procs.2022.12.028","journal-title":"Procedia Comput Sci"},{"key":"4894_CR7","doi-asserted-by":"publisher","unstructured":"Bodke CP, Patil DV, Gawande DR (2024) Stock Market Prediction Using Machine Learning: A Comprehensive Review with Emphasis on Long Short-Term Memory Techniques. https:\/\/doi.org\/10.5281\/zenodo.11213792","DOI":"10.5281\/zenodo.11213792"},{"key":"4894_CR8","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1016\/j.eswa.2017.02.044","volume":"80","author":"Y Chen","year":"2017","unstructured":"Chen Y, Hao Y (2017) A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction. Expert Syst Appl 80:340\u2013355","journal-title":"Expert Syst Appl"},{"key":"4894_CR9","doi-asserted-by":"publisher","unstructured":"Das S, Sahu TP, Janghel RR, Sahu BK (2022) Effective forecasting of stock market price by using extreme learning machine optimized by PSO-based group oriented crow search algorithm. In Neural Computing and Applications (Vol. 34, Issue 1). Springer London. https:\/\/doi.org\/10.1007\/s00521-021-06403-x","DOI":"10.1007\/s00521-021-06403-x"},{"key":"4894_CR10","doi-asserted-by":"crossref","unstructured":"Feurer M, Hutter F (2019) Hyperparameter optimization. Automated Machine Learning: Methods, Systems, Challenges, 3\u201333","DOI":"10.1007\/978-3-030-05318-5_1"},{"issue":"2","key":"4894_CR11","first-page":"103","volume":"1","author":"A Gani","year":"2008","unstructured":"Gani A, Ngassam C (2008) Effect of institutional factors on stock market development in Asia. Am J Finance Acc 1(2):103\u2013120","journal-title":"Am J Finance Acc"},{"key":"4894_CR12","doi-asserted-by":"publisher","unstructured":"Gong S, Zhang D, Du S, Jiu H, Zhou T (2021) An Empirical Analysis and Research on the prediction of Stock Trends based on the MLP neural network model. 2021 Int Conf Artif Intell Blockchain Technol (AIBT) 28\u201333. https:\/\/doi.org\/10.1109\/AIBT53261.2021.00012","DOI":"10.1109\/AIBT53261.2021.00012"},{"key":"4894_CR13","doi-asserted-by":"crossref","unstructured":"Heidari AA, Faris H, Mirjalili S, Aljarah I, Mafarja M (2020) Ant lion optimizer: theory, literature review, and application in multi-layer perceptron neural networks. Nature-Inspired Optimizers: Theor Literature Reviews Appl, 23\u201346","DOI":"10.1007\/978-3-030-12127-3_3"},{"key":"4894_CR14","unstructured":"Juare K, Kulkarni A (2023) Machine Learning Algorithms for Stock Market Prediction. International Journal of Innovative Science and Research Technology 7(12) 2193\u20132199. Retrieved from https:\/\/zenodo.org\/record\/7698476"},{"key":"4894_CR15","unstructured":"Kaies NCIBI (2022) F. G. Comparative study between the FLANN model and the MLP model in the stock market forecast: case of S & P 500. Journal of Positive School Psychology; Vol. 6 No. 6 (2022); 44\u201352; 2717\u20137564. Retrieved from https:\/\/journalppw.com\/index.php\/jpsp\/article\/view\/6880"},{"key":"4894_CR16","doi-asserted-by":"crossref","unstructured":"Karaboga D, Basturk B (2007) Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. International Fuzzy Systems Association World Congress (IFSA), Cancun, Mexico, pp 789\u2013798","DOI":"10.1007\/978-3-540-72950-1_77"},{"issue":"1","key":"4894_CR18","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1016\/j.asoc.2009.12.025","volume":"11","author":"D Karaboga","year":"2011","unstructured":"Karaboga D, Ozturk C (2011) A novel clustering approach: Artificial Bee colony (ABC) algorithm. Appl Soft Comput 11(1):652\u2013657","journal-title":"Appl Soft Comput"},{"key":"4894_CR17","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10462-012-9328-0","volume":"42","author":"D Karaboga","year":"2014","unstructured":"Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif Intell Rev 42:21\u201357","journal-title":"Artif Intell Rev"},{"issue":"2","key":"4894_CR19","first-page":"98","volume":"2","author":"S Khanderwal","year":"2021","unstructured":"Khanderwal S, Mohanty D (2021) Stock price prediction using ARIMA model. Int J Mark Hum Resource Res 2(2):98\u2013107","journal-title":"Int J Mark Hum Resource Res"},{"key":"4894_CR20","doi-asserted-by":"crossref","unstructured":"Kumar VU, Krishna A, Neelakanteswara P, Basha CZ (2020) Advanced prediction of performance of a student in an university using machine learning techniques. 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC), 121\u2013126","DOI":"10.1109\/ICESC48915.2020.9155557"},{"key":"4894_CR21","doi-asserted-by":"crossref","unstructured":"Li Z, Yu H, Xu J, Liu J, Mo Y (2023) Stock market analysis and prediction using LSTM: a case study on technology stocks. Innovations Appl Eng Technol, 1\u20136","DOI":"10.62836\/iaet.v2i1.162"},{"key":"4894_CR22","unstructured":"Menaka A, Raghu V, Dhanush BJ, Devaraju M, Kumar MA (2021) Stock Market Trend Prediction Using Hybrid Machine Learning Algorithms. International Journal of Recent Advances in Multidisciplinary Topics; Vol. 2 No. 4 (2021); 82\u201384; 2582\u20137839. Retrieved from https:\/\/journals.ijramt.com\/index.php\/ijramt\/article\/view\/643"},{"key":"4894_CR23","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.procs.2022.12.115","volume":"216","author":"LN Mintarya","year":"2023","unstructured":"Mintarya LN, Halim JNM, Angie C, Achmad S, Kurniawan A (2023) Machine learning approaches in stock market prediction: a systematic literature review. Procedia Comput Sci 216:96\u2013102","journal-title":"Procedia Comput Sci"},{"key":"4894_CR24","doi-asserted-by":"publisher","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":"4894_CR25","unstructured":"Mitchell M (1998) An introduction to genetic algorithms. MIT Press"},{"issue":"1","key":"4894_CR26","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1049\/cit2.12059","volume":"8","author":"S Mukherjee","year":"2023","unstructured":"Mukherjee S, Sadhukhan B, Sarkar N, Roy D, De S (2023) Stock market prediction using deep learning algorithms. CAAI Trans Intell Technol 8(1):82\u201394. https:\/\/doi.org\/10.1049\/cit2.12059","journal-title":"CAAI Trans Intell Technol"},{"key":"4894_CR27","doi-asserted-by":"publisher","first-page":"150199","DOI":"10.1109\/ACCESS.2020.3015966","volume":"8","author":"M Nabipour","year":"2020","unstructured":"Nabipour M, Nayyeri P, Jabani H, Shahab S, Mosavi A (2020) Predicting stock market trends using machine learning and deep learning algorithms via continuous and binary data; a comparative analysis. Ieee Access 8:150199\u2013150212","journal-title":"Ieee Access"},{"key":"4894_CR28","doi-asserted-by":"crossref","unstructured":"Nizar N, Zainudin AD, Albada A, Shan CM (2024) Forecasting Short-Term FTSE Bursa Malaysia Using WEKA. Information Management and Business Review; Vol 16 No 2(I)S (2024); 104\u2013114; 2220\u20133796; 10.22610\/Imbr.V16i2(I)S. Retrieved from https:\/\/ojs.amhinternational.com\/index.php\/imbr\/article\/view\/3773","DOI":"10.22610\/imbr.v16i2(I)S.3773"},{"issue":"4","key":"4894_CR29","doi-asserted-by":"publisher","first-page":"3007","DOI":"10.1007\/s10462-019-09754-z","volume":"53","author":"IK Nti","year":"2020","unstructured":"Nti IK, Adekoya AF, Weyori BA (2020) A systematic review of fundamental and technical analysis of stock market predictions. Artif Intell Rev 53(4):3007\u20133057","journal-title":"Artif Intell Rev"},{"issue":"1","key":"4894_CR30","first-page":"39","volume":"7","author":"H Oukhouya","year":"2023","unstructured":"Oukhouya H, Himdi E, K (2023) Comparing machine learning methods\u2014svr, xgboost, lstm, and mlp\u2014for forecasting the Moroccan stock market. Comput Sci Math Forum 7(1):39","journal-title":"Comput Sci Math Forum"},{"issue":"3","key":"4894_CR31","doi-asserted-by":"publisher","first-page":"2098","DOI":"10.1007\/s11227-017-2228-y","volume":"76","author":"X Pang","year":"2020","unstructured":"Pang X, Zhou Y, Wang P, Lin W, Chang V (2020) An innovative neural network approach for stock market prediction. J Supercomputing 76(3):2098\u20132118. https:\/\/doi.org\/10.1007\/s11227-017-2228-y","journal-title":"J Supercomputing"},{"key":"4894_CR32","doi-asserted-by":"publisher","unstructured":"Pardeshi K, Gill SS, Abdelmoniem AM (2023) Stock Market Price Prediction: a hybrid LSTM and sequential self-attention based Approach. https:\/\/doi.org\/10.48550\/arxiv.2308.04419","DOI":"10.48550\/arxiv.2308.04419"},{"key":"4894_CR33","doi-asserted-by":"publisher","unstructured":"Raju K, Chennakesavulu M, Saraswathi V, Rani BG, Sireesha R (2024) Enhancing stock market predictions: leveraging machine learning and Time Series Analysis for Accurate forecasting. https:\/\/doi.org\/10.5281\/zenodo.10940712","DOI":"10.5281\/zenodo.10940712"},{"key":"4894_CR34","doi-asserted-by":"publisher","unstructured":"Shah D, Isah H, Zulkernine F (2019) Stock market analysis: a review and taxonomy of prediction techniques. Int J Financial Stud 7(2). https:\/\/doi.org\/10.3390\/ijfs7020026","DOI":"10.3390\/ijfs7020026"},{"issue":"6","key":"4894_CR35","doi-asserted-by":"publisher","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"},{"key":"4894_CR36","doi-asserted-by":"publisher","unstructured":"Singh A, Bhardwaj G, Srivastava AP, Bindra A, Chaudhary P, Ritika (2022) Application of Network to Technical Analysis of Stock Market Prediction. 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM), 302\u2013306. https:\/\/doi.org\/10.1109\/ICIEM54221.2022.9853162","DOI":"10.1109\/ICIEM54221.2022.9853162"},{"issue":"1\u20134","key":"4894_CR37","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1016\/S0378-4371(00)00606-3","volume":"291","author":"X Sun","year":"2001","unstructured":"Sun X, Chen H, Wu Z, Yuan Y (2001) Multifractal analysis of Hang Seng index in Hong Kong stock market. Physica A 291(1\u20134):553\u2013562","journal-title":"Physica A"},{"issue":"4","key":"4894_CR38","doi-asserted-by":"publisher","first-page":"97","DOI":"10.14201\/ADCAIJ20198497116","volume":"8","author":"M Umer","year":"2019","unstructured":"Umer M, Awais M, Muzammul M (2019) Stock market prediction using machine learning (ML) algorithms. ADCAIJ: Adv Distrib Comput Artif Intell J 8(4):97\u2013116","journal-title":"ADCAIJ: Adv Distrib Comput Artif Intell J"},{"key":"4894_CR39","doi-asserted-by":"crossref","unstructured":"Upadhyay NK, Singh V, Singh S, Khanna P (2023) Enhancing Stock Market Predictability: A Comparative Analysis of RNN And LSTM Models for Retail Investors. Journal of Management and Service Science (JMSS); Vol. 3 No. 1 (2023); 1\u20139; 2583\u2013\u20091798. Retrieved from https:\/\/jmss.a2zjournals.com\/index.php\/mss\/article\/view\/42","DOI":"10.54060\/jmss.v3i1.42"},{"issue":"PA","key":"4894_CR40","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.iref.2023.07.083","volume":"89","author":"Y Xu","year":"2024","unstructured":"Xu Y, Liu J, Ma F, Chu J (2024) Liquidity and realized volatility prediction in Chinese stock market: a time-varying transitional dynamic perspective. Int Rev Econ Finance 89(PA):543\u2013560. https:\/\/doi.org\/10.1016\/j.iref.2023.07.083","journal-title":"Int Rev Econ Finance"},{"key":"4894_CR41","unstructured":"Yinka-Banjo C, Akinyemi M, Er-rabbany B (2023) Stock Market Prediction Using a Hybrid of Deep Learning Models. International Journal of Financial Studies, Economics and Management, Vol 2, Iss 2 (2023). Retrieved from https:\/\/doaj.org\/article\/6d8f3a41636b4e12a0ef712f72cfba32"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-024-04894-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-024-04894-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-024-04894-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T08:31:34Z","timestamp":1740817894000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-024-04894-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,16]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["4894"],"URL":"https:\/\/doi.org\/10.1007\/s12652-024-04894-9","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,16]]},"assertion":[{"value":"1 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}