https://m2.mtmt.hu/ eng 2026-04-15 05:57 BookChapter 34081594 VALIDATED true 0 false 2026-01-09T09:46:20.142+0000 2026-01-09T09:43:01.184+0000 2023-07-31T08:18:13.821+0000 true 10028399 Bereczki Bálint /api/admin/10028399 Admin Bálint Bereczki (ÓE 5 admin) true 10028399 2026-01-09T09:42:13.254+0000 2026-01-09T09:42:13.254+0000 2026-01-09T09:43:01.191+0000 true 10015207 Tamássyné T. Zsuzsa /api/admin/10015207 Admin Zsuzsa Tamássyné T. (OE admin) true 10015207 true false true 25 25 /api/publicationtype/25 PublicationType Chapter in Book 2 true 25 BookChapter true 10000312 Conference paper true 25 25 /api/publicationtype/25 PublicationType Chapter in Book 2 true 25 BookChapter /api/subtype/10000312 Konferenciaközlemény SubType Conference paper (Chapter in Book) 228 true 10000312 true 1 /api/category/1 Category Scientific true 1 Mosavi, Amirhosein 95 104 95 10 2023 Drought is among the most destructive natural disasters with a drastic impact on the economy, ecosystem, biodiversity, and agriculture. Climate change and global warming are greatly contributing in increasing the severity, irregularity, and frequency of droughts throughout the world. Accurate prediction of the droughts empowers the policies made for mitigation, resilience and adaptation. Machine learning models have shown outstanding performance with promising results in predicting the drought. This paper aims at presenting a systematics state of the art review on the major machine learning advancements using a novel taxonomy. Machine learning models have been classified in five major groups based on the method used, i.e., neural networks-based, decision tree-based, support vector-based, hybrids and ensembles. The survey shows that emerging ensemble and hybrid models deliver higher performance where single methods are often outperformed. true NATIONAL 2023 true true true true false false PAY 2026-01-09 false 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 false false false false 2023-10-29T10:05:23.890+0000 Szoftvertervezés- és Fejlesztés Intézet (ÓE / NIK) 2 16 1 2 0 true 297 true 10002 English /api/language/10002 Angol Language English true 2 false true 10939 true 10017 /api/country/10017 Country United States of America true 13 /api/city/10939 City Piscataway (NJ), United States of America true 2054246 true 27945264 IDENTICAL /api/publicationidentifier/27945264 https://doi.org/10.1109/INES59282.2023 10.1109/INES59282.2023 PublicationIdentifier DOI: 10.1109/INES59282.2023 true 6 DOI https://doi.org/@@@ /api/publicationsource/6 DOI PlainSource DOI true true 10001 /api/publicationsourcetype/10001 PublicationSourceType DOI true true 6 true false true 24216988 /api/publicationidentifier/24216988 https://www.worldcat.org/search?q=isbn%3A9798350328509 9798350328509 PublicationIdentifier ISBN: 9798350328509 true 122 ISBN https://www.worldcat.org/search?q=isbn%3A@@@ /api/publicationsource/122 ISBN PlainSource ISBN true true 10002 /api/publicationsourcetype/10002 PublicationSourceType Egyéb true false 122 true false true 24630939 /api/publicationidentifier/24630939 https://www.worldcat.org/search?q=isbn%3A9798350328516 9798350328516 PublicationIdentifier ISBN: 9798350328516 true 122 ISBN https://www.worldcat.org/search?q=isbn%3A@@@ /api/publicationsource/122 ISBN PlainSource ISBN true true 10002 /api/publicationsourcetype/10002 PublicationSourceType Egyéb true false 122 true false true 27945265 /api/publicationidentifier/27945265 https://www.worldcat.org/search?q=isbn%3A9798350328523 9798350328523 PublicationIdentifier ISBN: 9798350328523 true 122 ISBN https://www.worldcat.org/search?q=isbn%3A@@@ /api/publicationsource/122 ISBN PlainSource ISBN true true 10002 /api/publicationsourcetype/10002 PublicationSourceType Egyéb true false 122 true false /api/publication/34081522 Szakál Anikó. 27th IEEE International Conference on Intelligent Engineering Systems, INES 2023: Proceedings. (2023) ISBN:9798350328509; 9798350328516; 9798350328523 true true 23 23 /api/publicationtype/23 PublicationType Book 3 true 23 Book false true 34081522 true true true true true 10000144 Conference proceedings true 23 23 /api/publicationtype/23 PublicationType Book 3 true 23 Book /api/subtype/10000144 Konferenciakötet SubType Conference proceedings (Book) 345 true 10000144 false Book 2023 true 1 /api/category/1 Category Scientific true 1 false Language 10002 /api/language/10002 English Angol English true 2 true PersonAuthorship 109469235 /api/authorship/109469235 Mosavi, Amirhosein [Mosavi, Amirhosein (Natural Science), author] Szoftvertervezés- és Fejlesztés Intézet (ÓU / NJFCS) 1 0.5 true false Author 10050464 /api/author/10050464 Amirhosein Mosavi (Natural Science) Mosavi Amirhosein true 10050464 true Mosavi Amirhosein true false false AuthorshipType 1 /api/authorshiptype/1 Author 0 true 0 true false true PersonAuthorship 109469236 /api/authorship/109469236 Ardabili, Sina [Faizollahzadeh Ardabili, Sina (Artificial intell...), author] 2 0.5 false true Author 10103491 /api/author/10103491 Sina Faizollahzadeh Ardabili (Artificial intelligence) Faizollahzadeh Ardabili Sina true true Ardabili Sina true false false AuthorshipType 1 /api/authorshiptype/1 Author 0 true 0 true false true PublicationIdentifier 25863818 /api/publicationidentifier/25863818 DOI: 10.1109/INES59282.2023.10297771 PlainSource 6 /api/publicationsource/6 DOI PublicationSourceType 10001 /api/publicationsourcetype/10001 DOI true true true DOI DOI https://doi.org/@@@ true true 6 true PAY IDENTICAL 10.1109/INES59282.2023.10297771 https://doi.org/10.1109/INES59282.2023.10297771 false true PublicationIdentifier 25261574 /api/publicationidentifier/25261574 Scopus: 85178560143 PlainSource 3 /api/publicationsource/3 Scopus PublicationSourceType 10003 /api/publicationsourcetype/10003 Indexelő adatbázis false true true Scopus Scopus http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-@@@ true true 3 true IDENTICAL 85178560143 http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85178560143 true true PublicationIdentifier 25863819 /api/publicationidentifier/25863819 Other URL: https://ieeexplore.ieee.org/document/10297771 PlainSource 40 /api/publicationsource/40 Other URL PublicationSourceType 10006 /api/publicationsourcetype/10006 Link true true true Egyéb URL Other URL @@@ true true 40 true https://ieeexplore.ieee.org/document/10297771 https://ieeexplore.ieee.org/document/10297771 false true Classification 10059 /api/classification/10059 Data stream analysis true true Classification 10099 /api/classification/10099 Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) true true Classification 11816 /api/classification/11816 Surveillance of zones under humanitarian risk (migratory flow, drought,etc.) true true Classification 11603 /api/classification/11603 Artificial Intelligence & Decision support true true Keyword 3693 /api/keyword/3693 Artificial intelligence DUPLUM true 3693 true Keyword 1005305 /api/keyword/1005305 drought true 1005305 true Keyword 1281942 /api/keyword/1281942 big data true 1281942 true Keyword 1479886 /api/keyword/1479886 Data Science true 1479886 true Keyword 3155426 /api/keyword/3155426 deep learning true true /api/publication/34081594 Mosavi Amirhosein et al. Machine Learning for Drought Prediction; Review, Bibliometric Analysis, and Models Evaluation. (2023) In: 27th IEEE International Conference on Intelligent Engineering Systems, INES 2023 pp. 95-104<div class="BookChapter Publication long-list"> <div class="authors"> <img title="Forrásközlemény" style="float: left" src="/frontend/resources/grid/publication-core-icon.png"> <div class="autype autype0"> <span class="author-name" mtid="10050464"><a href="/gui2/?type=authors&mode=browse&sel=10050464" target="_blank">Mosavi Amirhosein (<span class="authorship-author-name">Mosavi Amirhosein</span> <span class="authorAux-mtmt"> Natural Science</span>) </a> </span> <span class="author-affil"><span title="Óbuda University">ÓU</span>/<span title="Neumann János Faculty of Informatics">NJFCS</span>/Szoftvertervezés- és Fejlesztés Intézet</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10103491"><a href="/gui2/?type=authors&mode=browse&sel=10103491" target="_blank">Ardabili Sina (<span class="authorship-author-name">Faizollahzadeh Ardabili Sina</span> <span class="authorAux-mtmt"> Artificial intelligence</span>) </a> </span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;34081594" target="_blank">Machine Learning for Drought Prediction; Review, Bibliometric Analysis, and Models Evaluation</a></div> <div class="InBook"><div class="chapter-in">In:</div> <div class="authors"> <div class="autype autype0"> <span class="author-name" mtid="10039071"><a href="/gui2/?type=authors&mode=browse&sel=10039071" target="_blank">Szakál Anikó (<span class="authorship-author-name">Szakál Anikó</span> <span class="authorAux-mtmt"> műszaki informatika</span>) </a> </span> <span class="author-affil">Óbuda University</span> </div> </div> <div class="booktitle"><a href="/gui2/?mode=browse&params=publication;34081522" target="_blank">27th IEEE International Conference on Intelligent Engineering Systems, INES 2023 : Proceedings </a></div> <div class="conference"> Conference: <span class="location">Nairobi, Kenya <span class="conference-date">2023.07.26. - 2023.07.31.</span> </div> <span class="editionNumber">(1)</span> <span class="publishedAt">Piscataway (NJ): <span class="publishers">IEEE Hungary Section</span>, <span class="page"> pp 95-104 </span> <span class="year">(2023)</span> ( <span class="seriesTitle">Proceedings - IEEE International Conference on Intelligent Engineering Systems</span> <span class="issn">1543-9259</span> ) </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Language: English | </span> <span class="identifiers"> <span class="id identifier oa_PAY" title=" Pay "> <a style="color:blue" title="10.1109/INES59282.2023.10297771" target="_blank" href="https://doi.org/10.1109/INES59282.2023.10297771"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="85178560143" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85178560143"> Scopus </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="https://ieeexplore.ieee.org/document/10297771" target="_blank" href="https://ieeexplore.ieee.org/document/10297771"> Other URL </a> </span> </span> <span class="bookchapter-ids">Book link(s):</span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="10.1109/INES59282.2023" target="_blank" href="https://doi.org/10.1109/INES59282.2023"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <span class="isbnOrIssn"> ISBN: </span> <a style="color:black" title="9798350328509" target="_blank" href="https://www.worldcat.org/search?q=isbn%3A9798350328509"> 9798350328509 </a> </span> <span class="id identifier oa_none" title="none"> <span class="isbnOrIssn"> ISBN: </span> <a style="color:black" title="9798350328516" target="_blank" href="https://www.worldcat.org/search?q=isbn%3A9798350328516"> 9798350328516 </a> </span> <span class="id identifier oa_none" title="none"> <span class="isbnOrIssn"> ISBN: </span> <a style="color:black" title="9798350328523" target="_blank" href="https://www.worldcat.org/search?q=isbn%3A9798350328523"> 9798350328523 </a> </span> </span> <div class="mtid"><span class="long-pub-mtid">Publication: 34081594</span> | <span class="status-data status-VALIDATED"> Validated </span> <span class="long-book-mtid">Book: 34081522</span> Core | <span class="type-subtype">Chapter in Book ( Conference paper ) </span> | <span class="pub-category">Scientific</span> | <span class="publication-sourceOfData">kézi felvitel</span> </div> <div class="lastModified">Last Modified: 2026.01.09. 10:43 Zsuzsa Tamássyné T. (OE admin) </div> </div> </div>