{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T09:53:44Z","timestamp":1742982824973,"version":"3.40.3"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031379390"},{"type":"electronic","value":"9783031379406"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-37940-6_18","type":"book-chapter","created":{"date-parts":[[2023,7,22]],"date-time":"2023-07-22T20:23:00Z","timestamp":1690057380000},"page":"215-227","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessment and Prediction of a Cyclonic Event: A Deep Learning Model"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6317-5620","authenticated-orcid":false,"given":"Susmita","family":"Biswas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9187-5918","authenticated-orcid":false,"given":"Mourani","family":"Sinha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,23]]},"reference":[{"key":"18_CR1","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3390\/fluids7010039","volume":"7","author":"D Adytia","year":"2022","unstructured":"Adytia, D., Saepudin, D., Pudjaprasetya, S.R., Husrin, S., Sopaheluwakan, A.A.: Deep learning approach for wave forecasting based on spatially correlated wind features, with a case study in the java sea, Indonesia. Fluids 7, 39 (2022). https:\/\/doi.org\/10.3390\/fluids7010039","journal-title":"Fluids"},{"key":"18_CR2","doi-asserted-by":"publisher","first-page":"419","DOI":"10.5194\/os-18-419-2022","volume":"18","author":"BJ Bethel","year":"2022","unstructured":"Bethel, B.J., Sun, W., Dong, C., Wang, D.: Forecasting hurricane-forced significant wave heights using a long short-term memory network in the Caribbean Sea. Ocean Sci. 18, 419\u2013436 (2022). https:\/\/doi.org\/10.5194\/os-18-419-2022","journal-title":"Ocean Sci."},{"issue":"2","key":"18_CR3","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1007\/s40808-020-00974-9","volume":"7","author":"S Biswas","year":"2020","unstructured":"Biswas, S., Sinha, M.: Performances of deep learning models for Indian Ocean wind speed prediction. Model. Earth Syst. Environ. 7(2), 809\u2013831 (2020). https:\/\/doi.org\/10.1007\/s40808-020-00974-9","journal-title":"Model. Earth Syst. Environ."},{"key":"18_CR4","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/978-3-031-22485-0_14","volume-title":"Artificial Intelligence: First International Symposium, ISAI 2022, Haldia, India, February 17\u201322, 2022, Revised Selected Papers","author":"S Biswas","year":"2022","unstructured":"Biswas, S., Sinha, M.: Assessment of shallow and deep learning models for prediction of sea surface temperature. In: Sk, A.A., Turki, T., Ghosh, T.K., Joardar, S., Barman, S. (eds.) Artificial Intelligence: First International Symposium, ISAI 2022, Haldia, India, February 17\u201322, 2022, Revised Selected Papers, pp. 145\u2013154. Springer Nature Switzerland, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-22485-0_14"},{"key":"18_CR5","doi-asserted-by":"publisher","first-page":"1107","DOI":"10.1093\/jcde\/qwac048","volume":"9","author":"V Domala","year":"2022","unstructured":"Domala, V., Lee, W.: Wave data prediction with optimized machine learning and deep learning techniques. J. Comput. Des. Eng. 9, 1107\u20131122 (2022). https:\/\/doi.org\/10.1093\/jcde\/qwac048","journal-title":"J. Comput. Des. Eng."},{"issue":"10","key":"18_CR6","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1109\/TNNLS.2016.2582924","volume":"28","author":"K Greff","year":"2017","unstructured":"Greff, K., Srivastava, R.K., Koutnik, J., Steunebrink, B.R., Schmidhuber, J.: LSTM: a search space odyssey. IEEE Trans. Neural Netw. Learning Syst. 28(10), 2222\u20132232 (2017). https:\/\/doi.org\/10.1109\/TNNLS.2016.2582924","journal-title":"IEEE Trans. Neural Netw. Learning Syst."},{"key":"18_CR7","doi-asserted-by":"publisher","first-page":"102151","DOI":"10.1016\/j.ocemod.2022.102151","volume":"181","author":"FC Minuzzi","year":"2023","unstructured":"Minuzzi, F.C., Farina, L.: A deep learning approach to predict significant wave height using long short-term memory. Ocean Model. 181, 102151 (2023). https:\/\/doi.org\/10.1016\/j.ocemod.2022.102151","journal-title":"Ocean Model."},{"key":"18_CR8","unstructured":"Patel, M., Patel, A., Ghosh, R.: Precipitation Nowcasting: Leveraging bidirectional LSTM and 1D CNN. arXiv:1810.10485 (cs) (2018)"},{"key":"18_CR9","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/j.rser.2019.01.014","volume":"104","author":"M Ali","year":"2019","unstructured":"Ali, M., Prasad, R.: Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition. Renew. Sustain. Energy Rev. 104, 281\u2013295 (2019). https:\/\/doi.org\/10.1016\/j.rser.2019.01.014","journal-title":"Renew. Sustain. Energy Rev."},{"key":"18_CR10","doi-asserted-by":"publisher","first-page":"1089357","DOI":"10.3389\/fmars.2023.1089357","volume":"10","author":"T Song","year":"2023","unstructured":"Song, T., Wang, J., Huo, J., Wei, W.: Prediction of significant wave height based on EEMD and deep learning. Front. Mar. Sci. 10, 1089357 (2023). https:\/\/doi.org\/10.3389\/fmars.2023.1089357","journal-title":"Front. Mar. Sci."},{"issue":"4","key":"18_CR11","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1016\/j.neunet.2005.06.042","volume":"80","author":"OP Singh","year":"2005","unstructured":"Singh, O.P., Khan, T.M.A., Sazedur Rahman, M.: Has the frequency of intense tropical cyclones increased in the north Indian Ocean. Current Sci. 80(4), 575\u2013580 (2005). https:\/\/doi.org\/10.1016\/j.neunet.2005.06.042","journal-title":"Current Sci."},{"issue":"6","key":"18_CR12","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1175\/1520-0485(1991)021<0782:ATGMFW>2.0.CO;2","volume":"21","author":"H Tolman","year":"1991","unstructured":"Tolman, H.: A third-generation model for wind waves on slowly varying, unsteady, and inhomogeneous depths and currents. J. Phys. Oceanogr. 21(6), 782\u2013797 (1991)","journal-title":"J. Phys. Oceanogr."},{"key":"18_CR13","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s12040-023-02058-5","volume":"132","author":"MS Afzal","year":"2023","unstructured":"Afzal, M.S., Kumar, L., Chugh, V., et al.: Prediction of significant wave height using machine learning and its application to extreme wave analysis. J. Earth Syst. Sci. 132, 51 (2023). https:\/\/doi.org\/10.1007\/s12040-023-02058-5","journal-title":"J. Earth Syst. Sci."}],"container-title":["Communications in Computer and Information Science","Advances in Computing and Data Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-37940-6_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,22]],"date-time":"2023-07-22T20:24:36Z","timestamp":1690057476000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-37940-6_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031379390","9783031379406"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-37940-6_18","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"23 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest:"}},{"value":"ICACDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advances in Computing and Data Sciences","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","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":"27 April 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 April 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icacds2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icacds.com\/","order":11,"name":"conference_url","label":"Conference URL","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":"Easychair & Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"464","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":"47","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":"10% - 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":"2","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)"}}]}}