Koromila Ioanna, N. Zoe, Giannakopoulos Theodoros, P. Stavros, Charou Eleni, Gyftakis Sotirios
{"title":"A dynamic model for environmentally safe shipping through the Aegean Sea","authors":"Koromila Ioanna, N. Zoe, Giannakopoulos Theodoros, P. Stavros, Charou Eleni, Gyftakis Sotirios","doi":"10.1109/IISA.2015.7388034","DOIUrl":null,"url":null,"abstract":"Aegean Sea is an extremely sensitive marine area anticipating a catastrophic event to occur any time now, owing both to hazardous vessel crossing its waters and the significant rise of the intensive traffic. This paper aims to present a probabilistic Bayesian model predicting the probability of a collision, contact or grounding occurrence in the Aegean Sea. The model takes into account the dynamic information of the navigation area and the prevailing weather conditions. The training of the network was performed using the data of the historical accident database of the Marine Rescue Coordination Centre, the National Meteorological Office of Greece and the Aminess database. The whole study has been run within the framework of the AMINESS project.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IISA.2015.7388034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Aegean Sea is an extremely sensitive marine area anticipating a catastrophic event to occur any time now, owing both to hazardous vessel crossing its waters and the significant rise of the intensive traffic. This paper aims to present a probabilistic Bayesian model predicting the probability of a collision, contact or grounding occurrence in the Aegean Sea. The model takes into account the dynamic information of the navigation area and the prevailing weather conditions. The training of the network was performed using the data of the historical accident database of the Marine Rescue Coordination Centre, the National Meteorological Office of Greece and the Aminess database. The whole study has been run within the framework of the AMINESS project.