dc.contributor.author | Kalibatienė, Diana | |
dc.contributor.author | Miliauskaitė, Jolanta | |
dc.date.accessioned | 2023-09-18T16:25:59Z | |
dc.date.available | 2023-09-18T16:25:59Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/113888 | |
dc.description.abstract | Nowadays, growing environmental pollution and human intervention in nature have increased the need to study and monitor these adverse effects in marine waters. Therefore, intelligent marine monitoring approaches with artificial intelligence (AI) methods are needed. Consequently, the main research questions arise how are AI and intelligent technologies applied in marine monitoring systems? How does it contribute to the sustainable development of the environment? To answer these questions, this paper presents the results of the systematic mapping (SM) of papers from Web of Science (WoS) and Scopus databases and develops a keyword map. SM results show that AI techniques are applied in the control, decision, simulation, and optimization of renewable energy in marine systems. The main finding is presented in the form of the keywords map, which indicates the main trends of sustainable development in renewable energy of marine systems applying AI. However, the effective application of AI techniques for sustainable development of energy in marine system should be analyzed further in detail. | eng |
dc.format | PDF | |
dc.format.extent | p. 1-6 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.rights | Laisvai prieinamas internete | |
dc.source.uri | https://icnae.selcuk.edu.tr/ICNAE_Proceedings.pdf | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:144545780/datastreams/MAIN/content | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:144545780/datastreams/COVER/content | |
dc.title | A survey on machine learning and fuzzy approaches for renewable energy in marine systems | |
dc.type | Straipsnis recenzuotame konferencijos darbų leidinyje / Paper published in peer-reviewed conference publication | |
dcterms.references | 21 | |
dc.type.pubtype | P1d - Straipsnis recenzuotame konferencijos darbų leidinyje / Article published in peer-reviewed conference proceedings | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Fundamentinių mokslų fakultetas / Faculty of Fundamental Sciences | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.studydirection | B04 - Informatikos inžinerija / Informatics engineering | |
dc.subject.vgtuprioritizedfields | IK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems | |
dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | fuzzy | |
dc.subject.en | machine learning | |
dc.subject.en | sustainable development | |
dc.subject.en | marine | |
dc.subject.en | buoys | |
dc.subject.en | renewable energy | |
dcterms.sourcetitle | 1 st International conference on new approaches in engineering (ICNAE'22), October 6-7, 2022, Konya, Turkey : proceedings | |
dc.publisher.name | Selcuk University | |
dc.publisher.city | Konya | |
dc.identifier.elaba | 144545780 | |