{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:27:05Z","timestamp":1775471225200,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031594618","type":"print"},{"value":"9783031594625","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-59462-5_12","type":"book-chapter","created":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T07:02:12Z","timestamp":1714633332000},"page":"173-185","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Comparing LSTM Models for\u00a0Stock Market Prediction: A Case Study with\u00a0Apple\u2019s Historical Prices"],"prefix":"10.1007","author":[{"given":"Ha Minh","family":"Tan","sequence":"first","affiliation":[]},{"given":"Le Gia","family":"Minh","sequence":"additional","affiliation":[]},{"given":"Tran Cao","family":"Minh","sequence":"additional","affiliation":[]},{"given":"Tran Thi Be","family":"Quyen","sequence":"additional","affiliation":[]},{"given":"Kien","family":"Cao-Van","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,3]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","unstructured":"AL-Alimi, D., et al.: Tlia: time-series forecasting model using long short-term memory integrated with artificial neural networks for volatile energy markets. Appl. Energy 343, 121230 (2023). https:\/\/doi.org\/10.1016\/j.apenergy.2023.121230","DOI":"10.1016\/j.apenergy.2023.121230"},{"issue":"2","key":"12_CR2","doi-asserted-by":"publisher","first-page":"43","DOI":"10.3390\/economies10020043","volume":"10","author":"GA Altarawneh","year":"2022","unstructured":"Altarawneh, G.A., Hassanat, A.B., Tarawneh, A.S., Abadleh, A., Alrashidi, M., Alghamdi, M.: Stock price forecasting for Jordan insurance companies amid the Covid-19 pandemic utilizing off-the-shelf technical analysis methods. Economies 10(2), 43 (2022)","journal-title":"Economies"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Ariyo, A.A., Adewumi, A.O., Ayo, C.K.: Stock price prediction using the Arima model. In: 2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation, pp. 106\u2013112. IEEE (2014)","DOI":"10.1109\/UKSim.2014.67"},{"key":"12_CR4","volume":"9","author":"HN Bhandari","year":"2022","unstructured":"Bhandari, H.N., Rimal, B., Pokhrel, N.R., Rimal, R., Dahal, K.R., Khatri, R.K.: Predicting stock market index using LSTM. Mach. Learn. App. 9, 100320 (2022)","journal-title":"Mach. Learn. App."},{"key":"12_CR5","doi-asserted-by":"publisher","unstructured":"Biswas, M., Shome, A., Islam, M.A., Nova, A.J., Ahmed, S.: Predicting stock market price: a logical strategy using deep learning. In: 2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), pp. 218\u2013223 (2021). https:\/\/doi.org\/10.1109\/ISCAIE51753.2021.9431817","DOI":"10.1109\/ISCAIE51753.2021.9431817"},{"key":"12_CR6","doi-asserted-by":"publisher","unstructured":"Chien, J.T., Misbullah, A.: Deep long short-term memory networks for speech recognition. In: 2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP), pp.\u00a01\u20135 (2016). https:\/\/doi.org\/10.1109\/ISCSLP.2016.7918375","DOI":"10.1109\/ISCSLP.2016.7918375"},{"key":"12_CR7","doi-asserted-by":"publisher","first-page":"184797901880867","DOI":"10.1177\/1847979018808673","volume":"10","author":"J Fattah","year":"2018","unstructured":"Fattah, J., Ezzine, L., Aman, Z., El Moussami, H., Lachhab, A.: Forecasting of demand using Arima model. Int. J. Eng. Bus. Manage. 10, 1847979018808673 (2018)","journal-title":"Int. J. Eng. Bus. Manage."},{"key":"12_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120346","volume":"227","author":"B G\u00fclmez","year":"2023","unstructured":"G\u00fclmez, B.: Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm. Expert Syst. Appl. 227, 120346 (2023)","journal-title":"Expert Syst. Appl."},{"key":"12_CR9","doi-asserted-by":"publisher","first-page":"202","DOI":"10.2307\/622202","volume":"3","author":"R Haining","year":"1978","unstructured":"Haining, R.: The moving average model for spatial interaction. Trans. Inst. Br. Geograph. 3, 202\u2013225 (1978)","journal-title":"Trans. Inst. Br. Geograph."},{"issue":"02","key":"12_CR10","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1142\/S0218488598000094","volume":"06","author":"S Hochreiter","year":"1998","unstructured":"Hochreiter, S.: The vanishing gradient problem during learning recurrent neural nets and problem solutions. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 06(02), 107\u2013116 (1998). https:\/\/doi.org\/10.1142\/S0218488598000094","journal-title":"Int. J. Uncertain. Fuzziness Knowl. Based Syst."},{"issue":"8","key":"12_CR11","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"12_CR12","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1016\/j.matpr.2021.04.154","volume":"81","author":"E Kasthuri","year":"2023","unstructured":"Kasthuri, E., Balaji, S.: Natural language processing and deep learning chatbot using long short term memory algorithm. Mater. Today Proc. 81, 690\u2013693 (2023)","journal-title":"Mater. Today Proc."},{"key":"12_CR13","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.: Stock price manipulation detection using deep unsupervised learning: the case of Thailand. IEEE Access 9, 106824\u2013106838 (2021)","journal-title":"IEEE Access"},{"key":"12_CR14","doi-asserted-by":"publisher","unstructured":"Md, A.Q., Kapoor, S., A.V., C.J., Sivaraman, A.K., Tee, K.F., H., S., N., J.: Novel optimization approach for stock price forecasting using multi-layered sequential LSTM. Appl. Soft Comput. 134, 109830 (2023). https:\/\/doi.org\/10.1016\/j.asoc.2022.109830, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1568494622008791","DOI":"10.1016\/j.asoc.2022.109830"},{"issue":"2","key":"12_CR15","first-page":"13","volume":"4","author":"P Mondal","year":"2014","unstructured":"Mondal, P., Shit, L., Goswami, S.: Study of effectiveness of time series modeling (Arima) in forecasting stock prices. Int. J. Comput. Sci. Eng. App. 4(2), 13 (2014)","journal-title":"Int. J. Comput. Sci. Eng. App."},{"key":"12_CR16","doi-asserted-by":"crossref","unstructured":"Tan, H.M., Wang, J.C.: Single channel speech separation using enhanced learning on embedding features. In: IEEE 10th Global Conference on Consumer Electronics (GCCE), pp. 430\u2013431. IEEE (2021)","DOI":"10.1109\/GCCE53005.2021.9621886"},{"key":"12_CR17","doi-asserted-by":"publisher","unstructured":"Vijh, M., Chandola, D., Tikkiwal, V., Kumar, A.: Stock closing price prediction using machine learning techniques. Proc. Comput. Sci. 167, 599\u2013606 (2020). https:\/\/doi.org\/10.1016\/j.procs.2020.03.326","DOI":"10.1016\/j.procs.2020.03.326"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Nature of Computation and Communication"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-59462-5_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T07:05:20Z","timestamp":1714633520000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-59462-5_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031594618","9783031594625"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-59462-5_12","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"value":"1867-8211","type":"print"},{"value":"1867-822X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 May 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICTCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Nature of Computation and Communication","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ho Chi Minh City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ictcc2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confy +","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"12","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}