{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T13:50:35Z","timestamp":1770040235431,"version":"3.49.0"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031493324","type":"print"},{"value":"9783031493331","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,12,22]],"date-time":"2023-12-22T00:00:00Z","timestamp":1703203200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,22]],"date-time":"2023-12-22T00:00:00Z","timestamp":1703203200000},"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\/978-3-031-49333-1_9","type":"book-chapter","created":{"date-parts":[[2023,12,21]],"date-time":"2023-12-21T11:02:29Z","timestamp":1703156549000},"page":"116-127","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Data-Driven and\u00a0Model-Driven Approaches in\u00a0Predictive Modelling for\u00a0Operational Efficiency: Mining Industry Use Case"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6706-8729","authenticated-orcid":false,"given":"Oussama","family":"Hasidi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"El Hassan","family":"Abdelwahed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"My Abdellah","family":"El Alaoui-Chrifi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aimad","family":"Qazdar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fran\u00e7ois","family":"Bourzeix","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Intissar","family":"Benzakour","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed","family":"Bendaouia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charifa","family":"Dahhassi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,22]]},"reference":[{"key":"9_CR1","doi-asserted-by":"crossref","unstructured":"Rueden, L., Mayer, S., Sifa, R., Bauckhage, C., Garcke, J.: Combining machine learning and simulation to a hybrid modelling approach: current and future directions. In: Advances In Intelligent Data Analysis XVIII, pp. 548\u2013560 (2020)","DOI":"10.1007\/978-3-030-44584-3_43"},{"key":"9_CR2","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.asoc.2016.03.013","volume":"44","author":"L Liao","year":"2016","unstructured":"Liao, L., K\u00f6ttig, F.: A hybrid framework combining data-driven and model-based methods for system remaining useful life prediction. Appl. Soft Comput. 44, 191\u2013199 (2016)","journal-title":"Appl. Soft Comput."},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Erge, O., Oort, E.: Combining physics-based and data-driven modelling in well construction: hybrid fluid dynamics modelling. J. Nat. Gas Sci. Eng. 97, 104348 (2022). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1875510021005436","DOI":"10.1016\/j.jngse.2021.104348"},{"key":"9_CR4","doi-asserted-by":"crossref","unstructured":"Song, H., Liu, X., Song, M.: Comparative study of data-driven and model-driven approaches in prediction of nuclear power plants operating parameters. Appl. Energy 341, 121077 (2023). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0306261923004415","DOI":"10.1016\/j.apenergy.2023.121077"},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"Zhang, S., et al.: Combing data-driven and model-driven methods for high proportion renewable energy distribution network reliability evaluation. Int. J. Electr. Power Energy Syst. 149, 108941 (2023). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0142061522009371","DOI":"10.1016\/j.ijepes.2022.108941"},{"key":"9_CR6","unstructured":"Michaud, L.: Froth Flotation: A Century of Innovation (2017). https:\/\/www.911metallurgist.com\/blog\/froth-flotation-century-innovation"},{"key":"9_CR7","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1007\/978-3-031-20490-6_26","volume-title":"Smart Applications and Data Analysis","author":"A Bendaouia","year":"2022","unstructured":"Bendaouia, A., et al.: Digital transformation of the flotation monitoring towards an online analyzer. In: Hamlich, M., Bellatreche, L., Siadat, A., Ventura, S. (eds.) SADASC 2022. Communications in Computer and Information Science, vol. 1677, pp. 325\u2013338. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20490-6_26"},{"key":"9_CR8","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1007\/978-3-031-20490-6_33","volume-title":"Smart Applications and Data Analysis","author":"O Hasidi","year":"2022","unstructured":"Hasidi, O., et al.: Digital Twins-Based Smart Monitoring and Optimisation of Mineral Processing Industry. In: Hamlich, M., Bellatreche, L., Siadat, A., Ventura, S. (eds.) SADASC 2022. Communications in Computer and Information Science, vol. 1677, pp. 411\u2013424. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20490-6_33"},{"key":"9_CR9","unstructured":"Roine, A.: HSC Chemistry\u00ae [Software], Metso Outotec, Pori (2021). Software available at www.mogroup.com\/hsc"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Sircar, A., Nair, A., Bist, N., Yadav, K.: Digital Twin in hydrocarbon industry. Petrol. Res. (2022)","DOI":"10.1016\/j.ptlrs.2022.04.001"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Qassimi, S., Abdelwahed, E.H.: Disruptive innovation in mining industry 4.0. Distrib. Sens. Intell. Syst. 313\u2013325 (2022)","DOI":"10.1007\/978-3-030-64258-7_28"}],"container-title":["Lecture Notes in Computer Science","Model and Data Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-49333-1_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,21]],"date-time":"2023-12-21T11:03:51Z","timestamp":1703156631000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-49333-1_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,22]]},"ISBN":["9783031493324","9783031493331"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-49333-1_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,22]]},"assertion":[{"value":"22 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MEDI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Model and Data Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sousse","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tunisia","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":"2 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"medi2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/medi2023.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"99","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":"27","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":"27% - 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":"4","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)"}}]}}